[R] [R-pkgs] New version of "catspec" package
I've uploaded a new version of "catspec" to CRAN. Catspec is for estimating certain "special categorical" models. It also contains "ctab", a function for creating one-way, two-way, and multi-way percentage tables (nothing special there really). Ctab can now print more than one percentage type, as well as table marginals. The first special model in catspec is "mclgen". Mclgen restructures a data frame so a multinomial logistic model can be estimated using a condition logit program. Doing so provides much more flexibility for imposing restrictions on the response variable. The second special (set of) models is "sqtab", for estimating loglinear models for square tables (aka "mobility models") such as symmetry, quasi-independence. One application can be to specify such models as multinomial logistic models with covariates, using mclgen. John Hendrickx ___ R-packages mailing list [EMAIL PROTECTED] https://stat.ethz.ch/mailman/listinfo/r-packages __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] Re: how to separate a string
To get the first character from a string, use substr(s, 1, 1) To split strings at a period, use strsplit(s, "\\.") (the period must be quoted, as "." matches anything in a regular expression). To get the index for "." in a string, see "?regexpr, but you will not need to do that if you use strsplit(). Cheers, Rich On 4/13/05, Cuichang Zhao <[EMAIL PROTECTED]> wrote: > hello, > i wonder how is string represent in R. if i have a string s= "hello", how > can i refer to first character in the string s? > also if i have s1 = "hello.1", s2 = "ok.1", how can i separate the s1 into > "hello" "1" and s2 into "ok" and "1"? I have tried to use the substring > function, but i don't where i can get the index for "." in the string? > > Thank you so much > > C-Ming > April 12, 2005 > > > - > > > [[alternative HTML version deleted]] > > __ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > -- Rich FitzJohn rich.fitzjohn gmail.com |http://homepages.paradise.net.nz/richa183 You are in a maze of twisty little functions, all alike __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] how to separate a string
hello, i wonder how is string represent in R. if i have a string s= "hello", how can i refer to first character in the string s? also if i have s1 = "hello.1", s2 = "ok.1", how can i separate the s1 into "hello" "1" and s2 into "ok" and "1"? I have tried to use the substring function, but i don't where i can get the index for "." in the string? Thank you so much C-Ming April 12, 2005 - [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] lm() with many responses
On Tue, 12 Apr 2005, John Pitney wrote:
I have one array of predictors, one observation per row, and one array of
responses, also arranged one observation per row. I arrange these into a
data.frame and call lm() with a pasted-together formula.
I would like to call lm() with a number of responses in excess of 100, but
for some reason, 39 seems to be a limit. Why do I get an "invalid variable
names" error from model.frame() when supplying 40 or more responses?
Your expression is too long. Create the response matrix and pass that to
the formula, rather than passing an expression.
There is a 500-char internal limit on variable names in
model.frame.default. That should be enough
As a workaround, I can loop through groups of 39 responses in separate
calls to lm(), but that seems inefficient and possibly version- or
platform-dependent.
Here is my best effort at a minimal example showing the problem.
It's not easy to cut-and-paste, though.
--- begin pasted R session ---
test.this <- function(n.resp, n.obs, n.pred) {
+ my.resp <- matrix(runif(n.resp * n.obs), nrow=n.obs)
+ my.resp.names <- paste("Response", 1:n.resp, sep=".")
+ my.pred <- matrix(runif(n.pred * n.obs), nrow=n.obs)
+ my.pred.names <- paste("Predictor", 1:n.pred, sep=".")
+ my.formula <- as.formula(paste("cbind(",
+ paste(my.resp.names, collapse=", "), ") ~ ",
+ paste(my.pred.names, collapse=" + ")))
+ d.tmp <- cbind(my.pred, my.resp)
+ d.tmp <- as.data.frame(d.tmp)
+ names(d.tmp) <- c(my.pred.names, my.resp.names)
+ my.lm <- lm(my.formula, data=d.tmp, model=F, qr=F, x=F, y=F,
+ na.action=na.exclude)
+ my.lm
+ }
# Now, try it. 39 response vectors is OK, but 40 causes an error:
m1 <- test.this(40, 10, 2)
Error in model.frame(formula, rownames, variables, varnames, extras,
extranames, :
invalid variable names
m1 <- test.this(39, 10, 2)
# No error for n.resp == 39.
# Also, shouldn't "qr=F" in the call to lm() turn off output of m1$qr?
Only if it were implemented.
# m1$qr exists. I'd like to save memory and omit it if possible.
str(m1$qr)
List of 5
$ qr : num [1:10, 1:3] -3.162 0.316 0.316 0.316 0.316 ...
..- attr(*, "dimnames")=List of 2
.. ..$ : chr [1:10] "1" "2" "3" "4" ...
.. ..$ : chr [1:3] "(Intercept)" "Predictor.1" "Predictor.2"
..- attr(*, "assign")= int [1:3] 0 1 2
$ qraux: num [1:3] 1.32 1.34 1.42
$ pivot: int [1:3] 1 2 3
$ tol : num 1e-07
$ rank : int 3
- attr(*, "class")= chr "qr"
# Here's my version:
version
_
platform i386-pc-mingw32
arch i386
os mingw32
system i386, mingw32
status
major2
minor0.1
year 2004
month11
day 15
language R
--- end pasted R session ---
Best regards,
John
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--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UKFax: +44 1865 272595
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Re: [R] pstoedit
On Wed, 13 Apr 2005, BORGULYA [iso-8859-2] Gábor wrote: Has onyone experience with "pstoedit" (http://www.pstoedit.net/pstoedit) to convert eps graphs generated by R on Linux to Windows formats (WMF or EMF)? Does this way work? Is there an other, better way? You can only do that using pstoedit on Windows. ^^ A much better way on Windows is to run the R code on R for Windows and use its win.metafile() device. Another better way is to use Adobe Illustrator. The ability to generate WMF on Unix is a long-standing wish at http://developer.r-project.org/WindowsTODO.html but no one has ever contributed a working device (although it would be no harder than say the PDF device). Note that because of font differences, conversion from EPS to WMF can only ever be approximate. The fact that the website of pstoedit mentions that a Better Enhanced Windows Meta Files (EMF) plugin exists for Windows 9x/NT/2K/XP only makes me expect poor quality. Am I right? No quality at all unless you are using Windows where it is unnecessary. -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UKFax: +44 1865 272595__ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] package submission and binary versions
On Tue, 12 Apr 2005, Peter E. Rossi wrote: From reading the CRAN web page, it appears that you should not submit precompiled binary versions of your package, but rather that these are built for you by someone working with CRAN. I submitted my package using R CMD build but without the binary flag on. I'd like to have a binary version available for Windows users. Should I submit a precompiled binary version as well? No, as it said. If your package passes its tests on those platforms, binary versions for Windows and MacOS X appear automatically (thanks to Uwe Ligges and Stefano Iacus). They even get updated for new R versions (and R 2.1.0 is imminent) when otherwise new submissions would be needed. (You could have asked [EMAIL PROTECTED] about CRAN questions rather than the world.) -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UKFax: +44 1865 272595 __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] A suggestion for predict function(s)
Maybe a useful addition to the predict functions would be to return the
values of the predictor variables. It just (unless there are problems)
requires an extra line. I have inserted an example below.
"predict.glm" <-
function (object, newdata = NULL, type = c("link", "response",
"terms"), se.fit = FALSE,
dispersion = NULL, terms = NULL,
na.action = na.pass, ...)
{
type <- match.arg(type)
na.act <- object$na.action
object$na.action <- NULL
if (!se.fit) {
if (missing(newdata)) {
pred <- switch(type, link = object$linear.predictors,
response = object$fitted, terms = predict.lm(object,
se.fit = se.fit, scale
= 1, type = "terms",
terms = terms))
if (!is.null(na.act))
pred <- napredict(na.act, pred)
}
else {
pred <- predict.lm(object, newdata, se.fit, scale = 1,
type = ifelse(type == "link", "response", type),
terms = terms, na.action = na.action)
switch(type, response = {
pred <- family(object)$linkinv(pred)
}, link = , terms = )
}
}
else {
if (inherits(object, "survreg"))
dispersion <- 1
if (is.null(dispersion) || dispersion == 0)
dispersion <- summary(object, dispersion = dispersion)$dispersion
residual.scale <- as.vector(sqrt(dispersion))
pred <- predict.lm(object, newdata, se.fit, scale = residual.scale,
type = ifelse(type == "link", "response", type),
terms = terms, na.action = na.action)
fit <- pred$fit
se.fit <- pred$se.fit
switch(type, response = {
se.fit <- se.fit * abs(family(object)$mu.eta(fit))
fit <- family(object)$linkinv(fit)
}, link = , terms = )
if (missing(newdata) && !is.null(na.act)) {
fit <- napredict(na.act, fit)
se.fit <- napredict(na.act, se.fit)
}
predictors <- if (missing(newdata)) model.matrix(object) else newdata
pred <- list(predictors=predictors,
fit = fit, se.fit = se.fit,
residual.scale = residual.scale)
}
pred
#__ end of R code
Ross Darnell
--
School of Health and Rehabilitation Sciences
University of Queensland, Brisbane QLD 4072 AUSTRALIA
Email: <[EMAIL PROTECTED]>
Phone: +61 7 3365 6087 Fax: +61 7 3365 4754 Room:822, Therapies Bldg.
http://www.shrs.uq.edu.au/shrs/school_staff/ross_darnell.html
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RE: [R] Why is 1 a double?
I'm not sure that this answers your questions but maybe they partly help.
p. 7 in An introduction to R notes
"For most purposes the user will not be concerned if the "numbers" in a numeric
vector
are integers, reals or even complex. Internally calculations are done as double
precision real
numbers, or double precision complex numbers if the input data are complex."
p. 13 of the R Language Definition notes
"Numeric calculations whose result is undefined, such as '0/0' produce (on
most, if not all,
platforms) the value NaN. This exists only in the double type."
p. 164 of the Reference manual notes
"Integer vectors exist so that data can be passed to C or Fortran code which
expects them, and so that
small integer data can be represented exactly and compactly.
Note that on almost all implementations of R the range of representable
integers is restricted to
about ±2 × 109: doubles can hold much larger integers exactly."
Tom
> -Original Message-
> From: Vivek Rao [mailto:[EMAIL PROTECTED]
> Sent: Wednesday, 13 April 2005 10:12 AM
> To: r-help@stat.math.ethz.ch
> Subject: [R] Why is 1 a double?
>
>
> Based on examples in R books and the syntax of other
> programming languages, I expected that
>
> n <- 10
>
> assigns the integer 10 to n, but typeof(n) is actually
> a double. The subscripting expression x[1] is valid,
> but sprintf("\n %d",1) is not, giving the error
>
> Error in sprintf("\n %d", 1) : use format %f, %e or %g
> for numeric objects
>
> One must use instead sprintf("\n %d",as.integer(1)).
>
> Two questions:
>
> (1) When one intends to define an integer variable,
> should a construction such as
>
> n <- as.integer(10)
>
> be used? Most examples I have seen don't do this.
>
> (2) Why wasn't the S language defined so that
> typeof(1) is "integer" rather than "double"?
>
> __
> R-help@stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide!
> http://www.R-project.org/posting-guide.html
>
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[R] package submission and binary versions
Dear r-help- >From reading the CRAN web page, it appears that you should not submit precompiled binary versions of your package, but rather that these are built for you by someone working with CRAN. I submitted my package using R CMD build but without the binary flag on. I'd like to have a binary version available for Windows users. Should I submit a precompiled binary version as well? many thanks! peter r Peter E. Rossi Joseph T. Lewis Professor of Marketing and Statistics Editor, Quantitative Marketing and Economics Rm 360, Graduate School of Business, U of Chicago 5807 S. Woodlawn Ave, Chicago IL 60637 Tel: (773) 702-7513 | Fax: (773) 834-2081 [EMAIL PROTECTED] WWW: http://ChicagoGsb.edu/fac/peter.rossi SSRN: http://ssrn.com/author=22862 QME: http://www.kluweronline.com/issn/1570-7156 __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] Why is 1 a double?
Based on examples in R books and the syntax of other
programming languages, I expected that
n <- 10
assigns the integer 10 to n, but typeof(n) is actually
a double. The subscripting expression x[1] is valid,
but sprintf("\n %d",1) is not, giving the error
Error in sprintf("\n %d", 1) : use format %f, %e or %g
for numeric objects
One must use instead sprintf("\n %d",as.integer(1)).
Two questions:
(1) When one intends to define an integer variable,
should a construction such as
n <- as.integer(10)
be used? Most examples I have seen don't do this.
(2) Why wasn't the S language defined so that
typeof(1) is "integer" rather than "double"?
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Re: [R] Time series misalignment
Thanks, Achim, I managed to do what I wanted, thanks to your suggestion, except for one thing. When I called ts.intersect I could only provide numerical arguments (more precisely, objects that can be coerced into time series, I guess). That means I was not able to pass the original row.names that I had read into a data frame (those were character strings). At that point those row.names became misaligned with the data frame created by the ts.intersect call, whose row names were just 1, 2, 3, Is there a way to avoid this problem? I will check the zoo package, but I started with R three days ago, so it's a bit of information overload right now. Thanks for the help. FS On 4/12/05, Achim Zeileis <[EMAIL PROTECTED]> wrote: > On Tue, 12 Apr 2005 18:47:21 -0400 Fernando Saldanha wrote: > > > Can one also predetermine a set and then estimate all the models one > > wants to compare using the zoo package? > > Sure, you can merge() several series first and then pass this as the > data argument to lm(). See the vignette of the zoo package for more > examples. > > > Or can that be done only with the tseries package? > > Really, you are *not* using the tseries package here! > > (In the old days, the class "ts" and its methods used to be in the > package ts, but this was merged into stats long ago. tseries is an > entirely different package.) > Z > > > Thanks. > > > > FS > > > > On 4/12/05, Achim Zeileis <[EMAIL PROTECTED]> wrote: > > > Fernando: > > > > > > > This maybe a basic question, but I have spent several hours > > > > researching and I could not get an answer, so please bear with me. > > > > The problem is with time series in the package tseries. > > > > > > BTW: the `tseries' package is not involved here. > > > > > > > As the example > > > > below shows, the time series can get misaligned, so that bad > > > > results are obtained when doing regressions. > > > > > > lm() per se has only very limited support for time series > > > regression. Therefore, there are currently several tools under > > > development for addressing this issue. In particular, Gabor > > > Grothendieck and myself are working on different approaches to this > > > problem. > > > > > > > > > > > > > To fix this problem I did the following: > > > > > > > > > tsf <- ts.intersect(y1, x1, z1) > > > > > > > > Now I can do: > > > > > > > > > lm1 <- lm(tsf[,3] ~ tsf[,2]) > > > > > > It is probably simpler to just do > > > lm1 <- lm(z1 ~ x1, data = tsf) > > > > > > Another approach is implemented in the zoo package. This implements > > > an formula dispatch and you can do > > > lm1 <- lm(I(z1 ~ x1)) > > > *without* computing tsf first. > > > > > > Depending on what you want to do with the fitted models, one of the > > > two approaches might be easier, currently. In particular, if you > > > want to fit and compare several models, then I would compute the > > > intersection first and fit all models of interest on this data set. > > > > > > Furthermore, note that the dispatch implementation via I() in zoo is > > > still under development and likely to change in future versions. > > > (But this mainly means that improved implementations will become > > > available soon, stay tuned :-) > > > Z > > > > > > > > > __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] lm() with many responses
Hi all,
I have one array of predictors, one observation per row, and one array
of responses, also arranged one observation per row. I arrange these
into a data.frame and call lm() with a pasted-together formula.
I would like to call lm() with a number of responses in excess of 100,
but for some reason, 39 seems to be a limit. Why do I get an "invalid
variable names" error from model.frame() when supplying 40 or more
responses? As a workaround, I can loop through groups of 39 responses
in separate calls to lm(), but that seems inefficient and possibly
version- or platform-dependent.
Here is my best effort at a minimal example showing the problem.
--- begin pasted R session ---
> test.this <- function(n.resp, n.obs, n.pred) {
+ my.resp <- matrix(runif(n.resp * n.obs), nrow=n.obs)
+ my.resp.names <- paste("Response", 1:n.resp, sep=".")
+ my.pred <- matrix(runif(n.pred * n.obs), nrow=n.obs)
+ my.pred.names <- paste("Predictor", 1:n.pred, sep=".")
+ my.formula <- as.formula(paste("cbind(",
+ paste(my.resp.names, collapse=", "), ") ~ ",
+ paste(my.pred.names, collapse=" + ")))
+ d.tmp <- cbind(my.pred, my.resp)
+ d.tmp <- as.data.frame(d.tmp)
+ names(d.tmp) <- c(my.pred.names, my.resp.names)
+ my.lm <- lm(my.formula, data=d.tmp, model=F, qr=F, x=F, y=F,
+ na.action=na.exclude)
+ my.lm
+ }
> # Now, try it. 39 response vectors is OK, but 40 causes an error:
> m1 <- test.this(40, 10, 2)
Error in model.frame(formula, rownames, variables, varnames, extras,
extranames, :
invalid variable names
> m1 <- test.this(39, 10, 2)
> # No error for n.resp == 39.
> # Also, shouldn't "qr=F" in the call to lm() turn off output of m1$qr?
> # m1$qr exists. I'd like to save memory and omit it if possible.
> str(m1$qr)
List of 5
$ qr : num [1:10, 1:3] -3.162 0.316 0.316 0.316 0.316 ...
..- attr(*, "dimnames")=List of 2
.. ..$ : chr [1:10] "1" "2" "3" "4" ...
.. ..$ : chr [1:3] "(Intercept)" "Predictor.1" "Predictor.2"
..- attr(*, "assign")= int [1:3] 0 1 2
$ qraux: num [1:3] 1.32 1.34 1.42
$ pivot: int [1:3] 1 2 3
$ tol : num 1e-07
$ rank : int 3
- attr(*, "class")= chr "qr"
> # Here's my version:
> version
_
platform i386-pc-mingw32
arch i386
os mingw32
system i386, mingw32
status
major2
minor0.1
year 2004
month11
day 15
language R
--- end pasted R session ---
Best regards,
John
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RE: [R] factors in multinom function (nnet)
Alexandre, I have a couple of remarks to make, not all of which you might find immediately helpful, I regret to say. * The choice between using predictors linearly or in factor versions is a modelling choice that is in no way specific to multinom. It is a general aspect of modelling that has to be faced in a whole variety of situations. Indeed the full spectrum of choices is much wider than this: linear, polynomials, splines, different sorts of splines, harmonic terms, factors, ... In fact the idea behind gam's was really to allow some of this extensive field of choices to be model driven, but I digress. Point 1: you need to learn about modelling first and then apply it to multinom. * It is curious to me that someone could be interested in multinomial models per se. Usually people have a context where multinomial models might be one approach to describing the situation in a statistically useful way. Another could be something like classification trees. The context is really what decides what modelling choices of this kind might be sensible. * There is an obvious suggestion for one reference, a certain notorious blue and yellow book for which multinom is part of the support software. I believe they discuss some of the alternatives as well, like classification trees, and some of the principles of modelling, but it's been a while since I read it... * Frank Harrell recently issued an excellent article on this list on brain surgery in a hurry to which you may usefully refer. I believe it was on April 1. Bill Venables. -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Alexandre Brito Sent: Wednesday, 13 April 2005 8:20 AM To: r-help@stat.math.ethz.ch Subject: [R] factors in multinom function (nnet) Dear All: I am interested in multinomial logit models (function multinon, library nnet) but I'm having troubles in choose whether to define the predictors as factors or not. I had posted earlier this example (thanks for the reply ronggui): worms <- data.frame(year = rep(2000:2004, c(3,3,3,3,3)), age = rep(1:3, 5), mud = c(2,5,0,8,7,7,5,9,14,12,8,7,5,13,11), sand = c(4,7,13,4,14,13,20,17,15,23,20,9,35,27,18), rocks = c(2,6,7,9,3,2,2,10,5,19,13,17,11,20,29)) k <- as.matrix(worms[,3:5]) (mud, sand and rocks are factors; age and year are predictors) Now there are several possibilities: m1 <- multinom(k ~ year+age, data = worms) m2 <- multinom(k ~ factor(year)+age, data = worms) m3 <- multinom(k ~ year+factor(age), data = worms) m4 <- multinom(k ~ factor(year)+factor(age), data = worms) m5 <- multinom(k ~ year:age, data = worms) m6 <- multinom(k ~ year*age, data = worms) m7 <- multinom(k ~ factor(year):age, data=worms) m8 <- multinom(k ~ year:factor(age), data=worms) and so on. I am far from an expert on this, and I would like to learn more about the utilization of multinom function in R and the kind of doubts I described above. So I hope that someone can recommend me some references in this matter (internet, books...) if any is available. Thanks in advance, best wishes Alexandre __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] Time series misalignment
On Tue, 12 Apr 2005 18:47:21 -0400 Fernando Saldanha wrote: > Can one also predetermine a set and then estimate all the models one > wants to compare using the zoo package? Sure, you can merge() several series first and then pass this as the data argument to lm(). See the vignette of the zoo package for more examples. > Or can that be done only with the tseries package? Really, you are *not* using the tseries package here! (In the old days, the class "ts" and its methods used to be in the package ts, but this was merged into stats long ago. tseries is an entirely different package.) Z > Thanks. > > FS > > On 4/12/05, Achim Zeileis <[EMAIL PROTECTED]> wrote: > > Fernando: > > > > > This maybe a basic question, but I have spent several hours > > > researching and I could not get an answer, so please bear with me. > > > The problem is with time series in the package tseries. > > > > BTW: the `tseries' package is not involved here. > > > > > As the example > > > below shows, the time series can get misaligned, so that bad > > > results are obtained when doing regressions. > > > > lm() per se has only very limited support for time series > > regression. Therefore, there are currently several tools under > > development for addressing this issue. In particular, Gabor > > Grothendieck and myself are working on different approaches to this > > problem. > > > > > > > > > To fix this problem I did the following: > > > > > > > tsf <- ts.intersect(y1, x1, z1) > > > > > > Now I can do: > > > > > > > lm1 <- lm(tsf[,3] ~ tsf[,2]) > > > > It is probably simpler to just do > > lm1 <- lm(z1 ~ x1, data = tsf) > > > > Another approach is implemented in the zoo package. This implements > > an formula dispatch and you can do > > lm1 <- lm(I(z1 ~ x1)) > > *without* computing tsf first. > > > > Depending on what you want to do with the fitted models, one of the > > two approaches might be easier, currently. In particular, if you > > want to fit and compare several models, then I would compute the > > intersection first and fit all models of interest on this data set. > > > > Furthermore, note that the dispatch implementation via I() in zoo is > > still under development and likely to change in future versions. > > (But this mainly means that improved implementations will become > > available soon, stay tuned :-) > > Z > > > > > __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] Time series misalignment
Can one also predetermine a set and then estimate all the models one wants to compare using the zoo package? Or can that be done only with the tseries package? Thanks. FS On 4/12/05, Achim Zeileis <[EMAIL PROTECTED]> wrote: > Fernando: > > > This maybe a basic question, but I have spent several hours > > researching and I could not get an answer, so please bear with me. The > > problem is with time series in the package tseries. > > BTW: the `tseries' package is not involved here. > > > As the example > > below shows, the time series can get misaligned, so that bad results > > are obtained when doing regressions. > > lm() per se has only very limited support for time series regression. > Therefore, there are currently several tools under development for > addressing this issue. In particular, Gabor Grothendieck and myself are > working on different approaches to this problem. > > > > > To fix this problem I did the following: > > > > > tsf <- ts.intersect(y1, x1, z1) > > > > Now I can do: > > > > > lm1 <- lm(tsf[,3] ~ tsf[,2]) > > It is probably simpler to just do > lm1 <- lm(z1 ~ x1, data = tsf) > > Another approach is implemented in the zoo package. This implements an > formula dispatch and you can do > lm1 <- lm(I(z1 ~ x1)) > *without* computing tsf first. > > Depending on what you want to do with the fitted models, one of the two > approaches might be easier, currently. In particular, if you want to fit > and compare several models, then I would compute the intersection first > and fit all models of interest on this data set. > > Furthermore, note that the dispatch implementation via I() in zoo is > still under development and likely to change in future versions. (But > this mainly means that improved implementations will become available > soon, stay tuned :-) > Z > > __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] Perhaps Off-topic lme question
A question on lme() : details: nlme() in R 2.1.0 beta or 2.0.1 The data,y, consisted of 82 data value in 5 groups of sizes 3 9 8 28 34 . I fit a simple one level random effects model by: myfit <- lme( y~1, rand = ~1|Group) The REML estimates of between and within Group effects are .0032 and .53, respectively; the between group component is essentially zero as is clearly evident from a plot of the data. So, thus far, no problem. However, the confidence interval for the between Groups sd that I get from intervals(myfit) goes from essentially 0 to infinity (6 x 10^13, actually). I assume that this is because the between component estimate is too close to the boundary of 0 so that the likelihood approximations with default control values fail, but I would appreciate a more definitive comment from someone who knows what they're talking about. If anyone cares to try this, the data in group order are below (i.e., first 3 from Group 1, next 9 from Group 2, etc.). Cheers to all, Bert Gunter 14.7 15.8 14.6 15.18 15.04 15.23 15.37 15.3 15.13 16.1 15.5 15.53 15.83 15.53 15.61 15.69 16.17 15.27 15.34 15.3 15.48 15.8 15.1 15.15 15.12 15.3 14.88 14.36 15.62 14.61 15.27 16.05 14.93 15.19 15.23 15.62 15.9 15.21 15.01 14.86 16.55 15.75 15.04 15.55 15.54 14.66 15.9 15.24 15.25 15.18 14.83 15.17 15.05 15.37 14.87 15.33 15.55 15.5 15.89 15.67 15.55 15.65 15.8 15.84 16.25 14.71 15.39 16.11 15.64 15.99 16.54 14.46 15.47 15.11 15.59 15.49 15.08 14.6 14.32 13.73 16.61 14.19 __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] pstoedit
Hi List! Has onyone experience with "pstoedit" (http://www.pstoedit.net/pstoedit) to convert eps graphs generated by R on Linux to Windows formats (WMF or EMF)? Does this way work? Is there an other, better way? The fact that the website of pstoedit mentions that a Better Enhanced Windows Meta Files (EMF) plugin exists for Windows 9x/NT/2K/XP only makes me expect poor quality. Am I right? Gábor __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] factors in multinom function (nnet)
Dear All: I am interested in multinomial logit models (function multinon, library nnet) but I'm having troubles in choose whether to define the predictors as factors or not. I had posted earlier this example (thanks for the reply ronggui): worms<- data.frame(year= rep(2000:2004, c(3,3,3,3,3)),age=rep(1:3,5), mud=c(2,5,0,8,7,7,5,9,14,12,8,7,5,13,11),sand=c(4,7,13,4,14,13,20,17,15,23,20,9,35,27,18), rocks=c(2,6,7,9,3,2,2,10,5,19,13,17,11,20,29)) k<- as.matrix(worms[,3:5]) (mud, sand and rocks are factors; age and year are predictors) Now there are several possibilities: m1<- multinom(k~year+age,data=worms) m2<- multinom(k~factor(year)+age,data=worms) m3<- multinom(k~year+factor(age),data=worms) m4<- multinom(k~factor(year)+factor(age),data=worms) m5<- multinom(k~year:age,data=worms) m6<- multinom(k~year*age,data=worms) m7<- multinom(k~factor(year):age,data=worms) m8<- multinom(k~year:factor(age),data=worms) and so on. I am far from an expert on this, and I would like to learn more about the utilization of multinom function in R and the kind of doubts I described above. So I hope that someone can recommend me some references in this matter (internet, books...) if any is available. Thanks in advance, best wishes Alexandre [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] Time series misalignment
Fernando: > This maybe a basic question, but I have spent several hours > researching and I could not get an answer, so please bear with me. The > problem is with time series in the package tseries. BTW: the `tseries' package is not involved here. > As the example > below shows, the time series can get misaligned, so that bad results > are obtained when doing regressions. lm() per se has only very limited support for time series regression. Therefore, there are currently several tools under development for addressing this issue. In particular, Gabor Grothendieck and myself are working on different approaches to this problem. > To fix this problem I did the following: > > > tsf <- ts.intersect(y1, x1, z1) > > Now I can do: > > > lm1 <- lm(tsf[,3] ~ tsf[,2]) It is probably simpler to just do lm1 <- lm(z1 ~ x1, data = tsf) Another approach is implemented in the zoo package. This implements an formula dispatch and you can do lm1 <- lm(I(z1 ~ x1)) *without* computing tsf first. Depending on what you want to do with the fitted models, one of the two approaches might be easier, currently. In particular, if you want to fit and compare several models, then I would compute the intersection first and fit all models of interest on this data set. Furthermore, note that the dispatch implementation via I() in zoo is still under development and likely to change in future versions. (But this mainly means that improved implementations will become available soon, stay tuned :-) Z __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] R into stata
library(foreign) ?write.dta Cheers, Rich On Apr 13, 2005 8:56 AM, Emre Ozaltin <[EMAIL PROTECTED]> wrote: > What is to command to change a dataset in R format "X.RData" into stata > format "X.dta"? > > Thank you, > > > --- > Emre Özaltin > Epidemiologist > Harvard Initiative for Global Health (HIGH) > 104 Mt. Auburn St. 02138 Cambridge, MA > tel: 1 (617) 495-4884 > fax: 1 (617) 495-8231 > email: [EMAIL PROTECTED] > > __ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html > -- Rich FitzJohn rich.fitzjohn gmail.com |http://homepages.paradise.net.nz/richa183 You are in a maze of twisty little functions, all alike __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] R into stata
What is to command to change a dataset in R format "X.RData" into stata format "X.dta"? Thank you, --- Emre Özaltin Epidemiologist Harvard Initiative for Global Health (HIGH) 104 Mt. Auburn St. 02138 Cambridge, MA tel: 1 (617) 495-4884 fax: 1 (617) 495-8231 email: [EMAIL PROTECTED] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] Time series misalignment
This maybe a basic question, but I have spent several hours researching and I could not get an answer, so please bear with me. The problem is with time series in the package tseries. As the example below shows, the time series can get misaligned, so that bad results are obtained when doing regressions. I found a way to do this correctly, but I find it rather cumbersome. My question is: is there a better way to do it? Thanks for any help. Suppose I define: > y1<-ts(c(1,2,3,5,7)) > x1<-diff(y1) > z1<-ts(c(1,1,2,2)) Then I get: > x1 Time Series: Start = 2 End = 5 Frequency = 1 [1] 1 1 2 2 > z1 Time Series: Start = 1 End = 4 Frequency = 1 [1] 1 1 2 2 Notice that the Start values for x1 and z1 are different. However, if I regress z1 on z1 I get: > reg1 <- lm(z1 ~ x1, na.action = NULL) > reg1 Call: lm(formula = z1 ~ x1, na.action = NULL) Coefficients: (Intercept) x1 01 But this is the wrong answer. The time series z1 and x1 are misaligned. lm is ignoring the fact that Start = 2 for x1 and Start = 1 for z1. To fix this problem I did the following: > tsf <- ts.intersect(y1, x1, z1) > tsf Time Series: Start = 2 End = 4 Frequency = 1 y1 x1 z1 2 2 1 1 3 3 1 2 4 5 2 2 These versions of z1 and x1 are correctly aligned. Now I can do: > lm1 <- lm(tsf[,3] ~ tsf[,2]) > lm1 Call: lm(formula = tsf[, 3] ~ tsf[, 2]) Coefficients: (Intercept) tsf[, 2] 1.0 0.5 This is the correct answer. However, it is rather cumbersome to refer to the aligned variables as columns of the time series object tsf. As an observation, I also called ts.intersect with the option dframe = t and got exactly the same results. So my question is: is there a less cumbersome way to keep these time series aligned? Thanks again for any help. __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] removing characters from a string
Thanks for all the helpful replies to my question about string handling. I will try to be more careful in making general comments about R, about which I still have much to learn. The string handling I need to do is not that sophisticated (somewhat contradicting my previous message) and can be done in Fortran 95 with "convenience" intrinsic functions such as INDEX, TRIM, ADJUSTL, SCAN, VERIFY . Figuring out the R equivalents using the functions cited in the replies will be a good exercise for me. __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
RE: [R] Fitting a mixed negative binomial model
This is a little bit tricky (nonlinear, mixed, count data ...) Off the top of my head, without even looking at the documentation, I think your best bet for this problem would be to use the weights statement to allow the variance to be proportional to the mean (and add a normal error term for individuals) -- this would be close to equivalent to the log-Poisson model used by Elston et al. (Parasitology 2001, 122, 563-569, "Analysis of aggregation, a worked example: numbers of ticks on red grouse chicks"), and might do what you want. -- 620B Bartram Hall[EMAIL PROTECTED] Zoology Department, University of Floridahttp://www.zoo.ufl.edu/bolker Box 118525 (ph) 352-392-5697 Gainesville, FL 32611-8525 (fax) 352-392-3704 __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] Any addtional information on Flexible Discriminant Analysis (fda)
Hi Everyone, I posted a similar, albiet more specific, question a while back and didnt get a response so I thought I'd try once more with a more general framing. Basically I'm wondering if anyone has any code, examples/illustrations, documentation (besides the basic R docs on mda/fda) relating to running the Tibshirani and Hastie "Flexible Discriminant Analysis" routine that they wouldnt mind pointing me to and/or sharing. Any information would be greatly appreciated, Many Thanks, Joe Retzer - [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
RE: [R] How to change letters after space into capital letters
This short function capitalizes the first letter of each word in a
character string, which is what I think you want.
capitalize <- function(x) {
x <- strsplit(x, " ")
for (i in seq(along = x)) {
substr(x[[i]], 1, 1) <- toupper(substr(x[[i]], 1, 1))
}
sapply(x, function(z) paste(z, collapse = " "))
}
Robert
-Original Message-
From: Wolfram Fischer [mailto:[EMAIL PROTECTED]
Sent: Monday, April 11, 2005 6:22 AM
To: r-help@stat.math.ethz.ch
Subject: [R] How to change letters after space into capital letters
What is the easiest way to change within vector of strings
each letter after a space into a capital letter?
E.g.:
c( "this is an element of the vector of strings", "second element" )
becomes:
c( "This Is An Element Of The Vector Of Strings", "Second Element" )
My reason to try to do this is to get more readable abbreviations.
(A suggestion would be to add an option to abbreviate() which changes
letters after space to uppercase letters before executing the
abbreviation
algorithm.)
Thanks - Wolfram
__
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RE: [R] R as programming language: references?
As far as predicting the number of copies which R will create during the execution of some code, that's almost completely implementation dependent; no language specification (syntax or semantics) would help. You can investigate this empirically (try several approaches and look at memory usage) and/or look at the relevant source (packages, the interface code for .C/.Call/.Fortran etc, the array manipulation routines,...). I should add that this code is surprisingly clear and modular, so it's much easier to read than you might think. Reid Huntsinger -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Jan T. Kim Sent: Tuesday, April 12, 2005 12:54 PM To: r-help@stat.math.ethz.ch Subject: Re: [R] R as programming language: references? On Tue, Apr 12, 2005 at 02:01:04PM +0200, A.J. Rossini wrote: > On Apr 12, 2005 11:54 AM, Duncan Murdoch <[EMAIL PROTECTED]> wrote: > > > > - Original Message - From: "Federico Calboli" > > > <[EMAIL PROTECTED]> > > > To: "r-help" > > > Sent: Tuesday, April 12, 2005 5:14 PM > > > Subject: [R] R as programming language: references? > > > > > > > > >> Hi All, > > >> > > >> I am looking for references on R as a programming language (apart form > > >> the standard R-lang.pdf and the other manuals), reference that would > > >> cover _in_depth_ things like loops, code optimisation, debugging tools > > >> etc... and is as up-to-date as possible. > > >> > > >> Can anyone suggest any book or other reference apart from the "green > > >> book" and the V&R "S-programming"? > > > > I think you've already got the best references. > > There is always the source. In a sense, it IS the most in-depth and > up-to-date description of the intricacies of using the language, > though it isn't as easy to read as V&R's S Programming. > > In-depth and up-to-date are tradeoffs rather than being complementary. I don't know what Federico Calboli has in mind, but as for myself, upon starting with R, I've been looking for an R language reference in the style of the Python reference (http://docs.python.org/ref/ref.html). The specification of the grammar and the associated semantics of a language gives me the kind of in-depth conceptual understanding that I like to have, and I find this more difficult to accrue for R than for other languages. For example, I'm still not certain whether I'm able to correctly predict how many copies of an object are created during the execution of some code, and consequently, I'm not really confident that my code is reasonably optimal. I'd appreciate pointers to any (more or less hidden) gems I may have overlooked, of course. Best regards, Jan -- +- Jan T. Kim ---+ |*NEW*email: [EMAIL PROTECTED] | |*NEW*WWW: http://www.cmp.uea.ac.uk/people/jtk | *-=< hierarchical systems are for files, not for humans >=-* __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] Cumulative Points and Confidence Interval Manipulation in barplot2
On Tue, 2005-04-12 at 10:14 -0500, Bret Collier wrote: > R-Users, > I am working with gplots (in gregmisc bundle) plotting some posterior > probabilities (using barplot2) of harvest bag limits for discrete data > (x-axis from 0 to 12, data is counts) and I ran into a couple of > questions whose solutions have evaded me. > > 1) When I create and include the confidence intervals, the lower bound > of the confidence intervals for several of the posterior probabilities > is below zero, and in those specific cases I only want to show the upper > limit for those CI's so they do not extend below the x-axis (as harvest > can not be <0). Also, comments on a better technique for CI > construction when the data is bounded to be >=0 would be appreciated. > > 2) I would also like to show the cumulative probability (as say a > point or line) across the range of the x-axis on the same figure at the > top, but I have been unable to figure out how to overlay a set of > cumulative points over the barplot across the same range as the x-axis. > > Below is some example code showing the test data I am working on > (xzero): > > xzero <- table(factor(WWNEW[HUNTTYPE=="DOVEONLY"], levels=0:12)) > > xzero > > 0 1 2 3 4 5 6 7 8 9 10 11 12 > 179 20 9 2 2 0 1 0 0 0 0 0 0 > > > n <- sum(xzero) > > k <- sum(table(xzero)) > > meantheta1 <-((2*xzero + 1)/(2*n + k)) > > vartheta1 > <-((2*(((2*n)+k)-((2*xzero)+1)))*((2*xzero)+1))/2*n)+k)^2)*(((2*n)+k)+2)) > > stderr <- sqrt(vartheta1) > > cl.l <- meantheta1-(stderr*2)#Fake CI: Test > > cl.u <- meantheta1+(stderr*2)#Fake CI: Test > > barplot2(meantheta1, xlab="WWD HARVEST DOVE ONLY 2001", > ylab="Probability", ylim=c(0, 1),xpd=F, col="blue", border="black", > axis.lty=1,plot.ci=TRUE, ci.u = cl.u, ci.l = cl.l) > > title(main="WHITE WING DOVE HARVEST PROBABILITIES: DOVE HUNT ONLY") > > > I would greatly appreciate any direction or assistance, > Thanks, > Bret Bret, If you replace the lower bound of your confidence intervals as follows, you can get just the upper bound plotted: cl.l.new <- ifelse(cl.l >= 0, cl.l, meantheta1) This will set the lower bound to meantheta1 in those cases, thus plotting the upper portion and you can remove the 'xpd=F' argument. Use 'ci.l = cl.l.new' here: barplot2(meantheta1, xlab="WWD HARVEST DOVE ONLY 2001", ylab="Probability", ylim=c(0, 1), col="blue", border="black", axis.lty=1,plot.ci=TRUE, ci.u = cl.u, ci.l = cl.l.new) I would defer to others with more Bayesian experience on alternatives for calculating bounded CI's for the PP's. With respect to the cumulative probabilities, if I am picturing the same thing you are, you can use the cumsum() function and then add points and/or a line as follows: points(cumsum(meantheta1), pch = 19) lines(cumsum(meantheta1), lty = "solid") See ?cumsum, ?points and ?lines for more information. BTW, some strategically placed spaces would help make your code a bit more readable for folks. HTH, Marc Schwartz __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] R as programming language: references?
On Tue, Apr 12, 2005 at 02:01:04PM +0200, A.J. Rossini wrote: > On Apr 12, 2005 11:54 AM, Duncan Murdoch <[EMAIL PROTECTED]> wrote: > > > > - Original Message - From: "Federico Calboli" > > > <[EMAIL PROTECTED]> > > > To: "r-help" > > > Sent: Tuesday, April 12, 2005 5:14 PM > > > Subject: [R] R as programming language: references? > > > > > > > > >> Hi All, > > >> > > >> I am looking for references on R as a programming language (apart form > > >> the standard R-lang.pdf and the other manuals), reference that would > > >> cover _in_depth_ things like loops, code optimisation, debugging tools > > >> etc... and is as up-to-date as possible. > > >> > > >> Can anyone suggest any book or other reference apart from the "green > > >> book" and the V&R "S-programming"? > > > > I think you've already got the best references. > > There is always the source. In a sense, it IS the most in-depth and > up-to-date description of the intricacies of using the language, > though it isn't as easy to read as V&R's S Programming. > > In-depth and up-to-date are tradeoffs rather than being complementary. I don't know what Federico Calboli has in mind, but as for myself, upon starting with R, I've been looking for an R language reference in the style of the Python reference (http://docs.python.org/ref/ref.html). The specification of the grammar and the associated semantics of a language gives me the kind of in-depth conceptual understanding that I like to have, and I find this more difficult to accrue for R than for other languages. For example, I'm still not certain whether I'm able to correctly predict how many copies of an object are created during the execution of some code, and consequently, I'm not really confident that my code is reasonably optimal. I'd appreciate pointers to any (more or less hidden) gems I may have overlooked, of course. Best regards, Jan -- +- Jan T. Kim ---+ |*NEW*email: [EMAIL PROTECTED] | |*NEW*WWW: http://www.cmp.uea.ac.uk/people/jtk | *-=< hierarchical systems are for files, not for humans >=-* __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] functions(t.test) on variables by groups
Dear R users,
I have a data frame with categorical Vars. "Groups"
and a couple columns of numeric Vars. I am trying to
make two-sample t.test on each variable(s01-s03) by
Groups.
A data generated as following:
zot <- data.frame(Groups=rep(letters[1:2], each=4),
s01=rnorm(8), s02=rnorm(8), s03=rnorm(8))
I have written a piece with a for loop.
for (i in 1:(length(zot)-1)) {
print(t.test(zot[,i+1]~zot[,1]))
}
I wish something can be easier extracted or can save
it within for loop, or not even using for loop.
Thanks in advance for your help.
Kevin
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Re: [R] not plotting when non-existent
On Tue, 12 Apr 2005 16:08:54 +0100 Luis Ridao Cruz wrote: > R-help, > > I'm trying to plot the following: > > year lgd > 1 1986 136.97479 > 2 1987 69.10377 > 3 1988 67.66744 > 4 1989 71.60316 > 5 1990 62.06897 > 6 1992 6.25000 > 7 1993 27.72021 > 8 1995 23.83648 > 9 1996 10.29412 > 10 1997 95.67487 > 11 1998 82.09367 > 12 1999 56.60401 > 13 2000 29.80864 > 14 2001 23.77535 > 15 2002 48.30378 > 16 2003 83.47571 > 17 2004 74.58711 > > There are 2 missing years 1991 and 1994. > Is it possible to plot this simple data set so that there is not > "line" connection between > 1990-1992 and 1993-1995? I would store the data as a "ts" object with NAs in it. If x is the "data.frame" above, you could do ## create regular time scale y <- data.frame(year = 1986:2004) ## merge data lgd <- merge(x, y, by = "year", all = TRUE)[,2] ## create ts object lgd <- ts(lgd, start = 1986) ## plot plot(lgd, type = "o", pch = 16) hth, Z > I currently use 'plot(, type = "o", pch = 16)' > > I could as well plot 'pieces' of the vectors with "lines" but I was > wondering wether there is a simple function to achieve this. > > I run on Windows XP > > > version > _ > platform i386-pc-mingw32 > arch i386 > os mingw32 > system i386, mingw32 > status > major2 > minor0.1 > year 2004 > month11 > day 15 > language R > > Thank you in advance > > __ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] Cumulative Points and Confidence Interval Manipulation in barplot2
R-Users, I am working with gplots (in gregmisc bundle) plotting some posterior probabilities (using barplot2) of harvest bag limits for discrete data (x-axis from 0 to 12, data is counts) and I ran into a couple of questions whose solutions have evaded me. 1) When I create and include the confidence intervals, the lower bound of the confidence intervals for several of the posterior probabilities is below zero, and in those specific cases I only want to show the upper limit for those CI's so they do not extend below the x-axis (as harvest can not be <0). Also, comments on a better technique for CI construction when the data is bounded to be >=0 would be appreciated. 2) I would also like to show the cumulative probability (as say a point or line) across the range of the x-axis on the same figure at the top, but I have been unable to figure out how to overlay a set of cumulative points over the barplot across the same range as the x-axis. Below is some example code showing the test data I am working on (xzero): xzero <- table(factor(WWNEW[HUNTTYPE=="DOVEONLY"], levels=0:12)) > xzero 0 1 2 3 4 5 6 7 8 9 10 11 12 179 20 9 2 2 0 1 0 0 0 0 0 0 > n <- sum(xzero) > k <- sum(table(xzero)) > meantheta1 <-((2*xzero + 1)/(2*n + k)) > vartheta1 <-((2*(((2*n)+k)-((2*xzero)+1)))*((2*xzero)+1))/2*n)+k)^2)*(((2*n)+k)+2)) > stderr <- sqrt(vartheta1) > cl.l <- meantheta1-(stderr*2)#Fake CI: Test > cl.u <- meantheta1+(stderr*2)#Fake CI: Test > barplot2(meantheta1, xlab="WWD HARVEST DOVE ONLY 2001", ylab="Probability", ylim=c(0, 1),xpd=F, col="blue", border="black", axis.lty=1,plot.ci=TRUE, ci.u = cl.u, ci.l = cl.l) > title(main="WHITE WING DOVE HARVEST PROBABILITIES: DOVE HUNT ONLY") I would greatly appreciate any direction or assistance, Thanks, Bret platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major2 minor0.1 year 2004 month11 day 15 language R *Note: I am working in Exmacs __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] not plotting when non-existent
Luis Ridao Cruz wrote on 4/12/2005 10:08 AM: R-help, I'm trying to plot the following: year lgd 1 1986 136.97479 2 1987 69.10377 3 1988 67.66744 4 1989 71.60316 5 1990 62.06897 6 1992 6.25000 7 1993 27.72021 8 1995 23.83648 9 1996 10.29412 10 1997 95.67487 11 1998 82.09367 12 1999 56.60401 13 2000 29.80864 14 2001 23.77535 15 2002 48.30378 16 2003 83.47571 17 2004 74.58711 There are 2 missing years 1991 and 1994. Is it possible to plot this simple data set so that there is not "line" connection between 1990-1992 and 1993-1995? I currently use 'plot(, type = "o", pch = 16)' I could as well plot 'pieces' of the vectors with "lines" but I was wondering wether there is a simple function to achieve this. I run on Windows XP version _ platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major2 minor0.1 year 2004 month11 day 15 language R Thank you in advance Luis, Place an NA for 1991 and 1994. missingData <- data.frame(year = c(1991, 1994), lgd = rep(NA, 2)) newData <- rbind(oldData, missingData) newData <- newData[order(newData$year), ] plot(lgd ~ year, newData, type = "o") HTH, --sundar __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] not plotting when non-existent
R-help, I'm trying to plot the following: year lgd 1 1986 136.97479 2 1987 69.10377 3 1988 67.66744 4 1989 71.60316 5 1990 62.06897 6 1992 6.25000 7 1993 27.72021 8 1995 23.83648 9 1996 10.29412 10 1997 95.67487 11 1998 82.09367 12 1999 56.60401 13 2000 29.80864 14 2001 23.77535 15 2002 48.30378 16 2003 83.47571 17 2004 74.58711 There are 2 missing years 1991 and 1994. Is it possible to plot this simple data set so that there is not "line" connection between 1990-1992 and 1993-1995? I currently use 'plot(, type = "o", pch = 16)' I could as well plot 'pieces' of the vectors with "lines" but I was wondering wether there is a simple function to achieve this. I run on Windows XP > version _ platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major2 minor0.1 year 2004 month11 day 15 language R Thank you in advance __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] lme problem
Sorry for the long letter! I have recently started using R. For the start I have tried to repeat examples from Milliken & Johnson "Analysis of Messy Data - Analysis of Covariance", but I can not replicate it in R. The example is chocolate chip experiment. Response variable vas time to dissolve chocolate chip in seconds (time), covariate was time to dissolve butterscotch chip (bstime), and type was a type of chocolate chip. Problem is that I obtain different degrees of freedom compared to one in the book. Could it be sum of squares problem (type III vs. type I)? Milliken & Johnson use SAS for calculations and this is program the used: proc mixed data=mmacov method=type3; class type; model time=type bstime*type/solution noint. My R code is: LME.1=lme(time~bstime:type+type-1,data=CCE,random=~1|type) and summary is: Value Std.Error DF t-valuep-value typeBlue M&M18.0 18.5 0 0.97 NaN typeButton21.6 14.1 0 1.53 NaN typeChoc Chip 16.9 17.7 0 0.96 NaN typeRed M&M26.6 16.0 0 1.66 NaN typeSmall M&M 22.2 30.5 0 0.73 NaN typeSnow Cap 8.7 13.1 0 0.67 NaN bstime:typeBlue M&M 1.1 0.6 24 1.72 0.098 bstime:typeButton 1.3 0.4 24 3.57 0.002 bstime:typeChoc Chip 1.2 0.7 24 1.60 0.123 bstime:typeRed M&M 0.5 0.6 24 0.95 0.350 bstime:typeSmall M&M 0.2 1.0 24 0.19 0.848 bstime:typeSnow Cap 0.9 0.4 24 2.25 0.034 However in Milliken & Johnson all df are 23. Values (estimates) are almost identical, but there are some small differences in SE and t. Using anova(LME.1) I obtain numDF denDF F-value p-value type6 0 18.19 NaN bstime:type 624 4.04 0.0061 but in the book it is: numDF denDF F-value p-value type6 23 2.00 0.1075 bstime:type 6 23 4.04 0.0066 Data are at the end of the letter. I am not sure what I did wrong. Sincerely, Milos Zarkovic ** Milos Zarkovic MD, Ph.D. Associate Professor of Internal Medicine Institute of Endocrinology Dr Subotica 13 11000 Beograd Serbia Tel +381-63-202-925 Fax +381-11-685-357 Email [EMAIL PROTECTED] ** type,person,bstime,time Button,1,27,53 Choc Chip,2,17,36 Blue M&M,3,28,60 Blue M&M,4,30,45 Red M&M,5,20,30 Choc Chip,6,29,51 Small M&M,7,30,25 Button,8,16,47 Small M&M,9,32,25 Blue M&M,10,19,38 Blue M&M,11,33,48 Button,12,19,39 Snow Cap,13,15,20 Blue M&M,14,19,34 Choc Chip,15,20,40 Blue M&M,16,24,42 Snow Cap,17,21,29 Button,18,35,90 Red M&M,19,35,45 Small M&M,20,30,33 Button,21,34,65 Button,22,40,58 Small M&M,23,22,26 Snow Cap,24,16,23 Button,25,28,72 Blue M&M,26,25,48 Choc Chip,27,14,34 Button,28,23,45 Snow Cap,28,40,44 Blue M&M,30,28,48 Snow Cap,31,19,26 Snow Cap,32,21,29 Small M&M,33,32,30 Red M&M,34,16,32 Red M&M,35,19,47 __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] calling svydesign function that uses model.frame
On Mon, 11 Apr 2005, Richard Valliant wrote:
I need help on calling the svydesign function in the survey package
(although this error appears not to be specific to svydesign). I am
passing parameters incorrectly but am not sure how to correct the
problem.
## Call the main function PS.sim (one of mine). The dots are
parameters I omitted to simplify the question.
## y.col, str.col, clus.id, and PS.col are names of columns in the
object pop.
PS.sim(pop=small, y.col="NOTCOV",
...,str.col="new.str", clus.id="new.psu",
PS.col="PS.var", ...)
## A data.frame called sam.dat is generated by PS.sim. Its first 3
lines are:
ID new.str PS.var new.psu NOTCOV wts
213 1 32 2 37.7
236 1 32 2 37.7
286 1 22 2 37.7
I need to call svydesign with the parms I use to invoke the main
function PS.sim, i.e., ~clus.id and ~str.col.
How do I do that?
Two possibilities
1/ construct a formula with as.formula and paste
svydesign(id=as.formula(paste("~",new.psu)),
strata=as.formula(paste("~",str.col)),...)
For a working example
data(api)
psu<-"dnum"
svydesign(id=as.formula(paste("~",psu)), weight=~pw,data=apiclus1)
1 - level Cluster Sampling design
With (15) clusters.
svydesign(id = as.formula(paste("~", psu)), weight = ~pw, data = apiclus1)
2/ use substitute()
A working example:
psu<-"dnum"
eval(substitute(svydesign(id=~id,weight=~pw, data=apiclus1),
list(id=as.name(psu
1 - level Cluster Sampling design
With (15) clusters.
svydesign(id = ~dnum, weight = ~pw, data = apiclus1)
As you can see, the second option is probably more cumbersome but has the
advantage of producing a prettier-looking call.
-thomas
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Re: [R] removing characters from a string
Martin Maechler wrote: "Vivek" == Vivek Rao <[EMAIL PROTECTED]> on Tue, 12 Apr 2005 05:54:55 -0700 (PDT) writes: Vivek> Is there a simple way in R to remove all characters Vivek> from a string other than those in a specified set? For Vivek> example, I want to keep only the digits 0-9 in a Vivek> string. Vivek> In general, I have found the string handling abilities Vivek> of R a bit limited. (Of course it's great for stats in Vivek> general). Is there a good reference on this? Or should Vivek> R programmers dump their output to a text file and use Vivek> something like Perl or Python for sophisticated text Vivek> processing? Vivek> I am familiar with the basic functions such as nchar, Vivek> substring, as.integer, print, cat, sprintf etc. It depends on your "etc": The above is pretty trivial using gsub(), but since you sound sophisticated enough to proclaim missing R abilities, I leave the exercise to you. Part of the problem here is our help system. gsub is documented within the grep topic, so when you look at the keyword==character topics, you don't see it explicitly. (You do see "pattern matching and replacement", which should have been a hint.) And if you were looking for "string handling" under the programming category, you're completely out of luck. Another reason some people might see R's string handling as limited is that it is sometimes more cumbersome to manipulate strings in R than in other languages. For example, I vaguely recall that there's a good reason why R doesn't use "+" to concatenate strings, but I can't remember what it is. And sometimes I'd like to strip whitespace or pad things to a given width; I generally need to define my own functions to do that each time. R is capable of concatenation, stripping and padding, but is sometimes a little obscure in how it does them. Duncan Murdoch __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] where is internal function of sample()?
On Mon, 11 Apr 2005, Marc Schwartz wrote: A general pattern for C .Internal functions is to use a prefix of "do_" in conjunction with the R function name. So in this case, the C function is called do_sample and begins at line 391 (for 2.0.1 patched) in the aforementioned C source file. and in the case of the few exceptions to this rule you can look in names.c for a complete table. -thomas __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] removing characters from a string
Using help.start() and searching on keyword "character" or using help.search(keyword="character") will show you what you have missed. As others have pointed out, you have missed the power of regular expressions (despite that being how these things are done in Perl). Also, strsplit() can be very powerful. On Tue, 12 Apr 2005, Vivek Rao wrote: Is there a simple way in R to remove all characters from a string other than those in a specified set? For example, I want to keep only the digits 0-9 in a string. In general, I have found the string handling abilities of R a bit limited. Your exploration of them seems more than a bit limited. (Of course it's great for stats in general). Is there a good reference on this? Or should R programmers dump their output to a text file and use something like Perl or Python for sophisticated text processing? I am familiar with the basic functions such as nchar, substring, as.integer, print, cat, sprintf etc. -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UKFax: +44 1865 272595 __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] Re: residuals in VGAM
Try [EMAIL PROTECTED] -- Ferdinand Alimadhi Programmer / Analyst Harvard University The Institute for Quantitative Social Science (617) 496-0187 [EMAIL PROTECTED] www.iq.harvard.edu [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] removing characters from a string
Hi
Try
gsub("[^0-9]","","af-456utaDFasswe34534%^&%*$h567890ersdfg")
[1] "45634534567890"
HTH
rksh
On Apr 12, 2005, at 01:54 pm, Vivek Rao wrote:
Is there a simple way in R to remove all characters
from a string other than those in a specified set? For
example, I want to keep only the digits 0-9 in a
string.
In general, I have found the string handling abilities
of R a bit limited. (Of course it's great for stats in
general). Is there a good reference on this? Or should
R programmers dump their output to a text file and use
something like Perl or Python for sophisticated text
processing?
I am familiar with the basic functions such as nchar,
substring, as.integer, print, cat, sprintf etc.
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--
Robin Hankin
Uncertainty Analyst
Southampton Oceanography Centre
European Way, Southampton SO14 3ZH, UK
tel 023-8059-7743
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Re: [R] removing characters from a string
> "Vivek" == Vivek Rao <[EMAIL PROTECTED]> > on Tue, 12 Apr 2005 05:54:55 -0700 (PDT) writes: Vivek> Is there a simple way in R to remove all characters Vivek> from a string other than those in a specified set? For Vivek> example, I want to keep only the digits 0-9 in a Vivek> string. Vivek> In general, I have found the string handling abilities Vivek> of R a bit limited. (Of course it's great for stats in Vivek> general). Is there a good reference on this? Or should Vivek> R programmers dump their output to a text file and use Vivek> something like Perl or Python for sophisticated text Vivek> processing? Vivek> I am familiar with the basic functions such as nchar, Vivek> substring, as.integer, print, cat, sprintf etc. It depends on your "etc": The above is pretty trivial using gsub(), but since you sound sophisticated enough to proclaim missing R abilities, I leave the exercise to you. Martin __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
RE: [R] removing characters from a string
gsub("[^0-9]","","ab9c81")
HTH
--Bill
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Liaw, Andy
Sent: Tuesday, April 12, 2005 9:03 AM
To: 'Vivek Rao'; r-help@stat.math.ethz.ch
Subject: RE: [R] removing characters from a string
Just gsub() non-numerics with ""; e.g.:
> gsub("[a-zA-Z]", "", "aB9c81")
[1] "981"
[I'm really bad in regular expressions, and don't know how to construct
"non-numerics".]
Andy
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Re: [R] removing characters from a string
Liaw, Andy wrote:
Just gsub() non-numerics with ""; e.g.:
gsub("[a-zA-Z]", "", "aB9c81")
[1] "981"
[I'm really bad in regular expressions, and don't know how to construct
"non-numerics".]
Use a ^ to negate a character range:
> gsub("[^0-9]", "", "aB9c81")
[1] "981"
Baz
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RE: [R] removing characters from a string
Dear Vivek,
Actually, I think R has reasonably good facilities for manipulating strings.
See ?gsub etc.; for example:
gsub("[^0-9]", "", "XKa0&*1jk2")
[1] "012"
I hope this helps,
John
John Fox
Department of Sociology
McMaster University
Hamilton, Ontario
Canada L8S 4M4
905-525-9140x23604
http://socserv.mcmaster.ca/jfox
> -Original Message-
> From: [EMAIL PROTECTED]
> [mailto:[EMAIL PROTECTED] On Behalf Of Vivek Rao
> Sent: Tuesday, April 12, 2005 7:55 AM
> To: r-help@stat.math.ethz.ch
> Subject: [R] removing characters from a string
>
> Is there a simple way in R to remove all characters from a
> string other than those in a specified set? For example, I
> want to keep only the digits 0-9 in a string.
>
> In general, I have found the string handling abilities of R a
> bit limited. (Of course it's great for stats in general). Is
> there a good reference on this? Or should R programmers dump
> their output to a text file and use something like Perl or
> Python for sophisticated text processing?
>
> I am familiar with the basic functions such as nchar,
> substring, as.integer, print, cat, sprintf etc.
>
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Re: [R] removing characters from a string
On Tue, 2005-04-12 at 05:54 -0700, Vivek Rao wrote:
> Is there a simple way in R to remove all characters
> from a string other than those in a specified set? For
> example, I want to keep only the digits 0-9 in a
> string.
>
> In general, I have found the string handling abilities
> of R a bit limited. (Of course it's great for stats in
> general). Is there a good reference on this? Or should
> R programmers dump their output to a text file and use
> something like Perl or Python for sophisticated text
> processing?
>
> I am familiar with the basic functions such as nchar,
> substring, as.integer, print, cat, sprintf etc.
Something like the following should work:
> x <- paste(sample(c(letters, LETTERS, 0:9), 50, replace = TRUE),
collapse = "")
> x
[1] "QvuuAlSJYUFpUpwJomtCir8TfvNQyV6O7W7TlXSXlLHocCdtnV"
> gsub("[^0-9]", "", x)
[1] "8677"
The use of gsub() here replaces any characters NOT in 0:9 with a "",
therefore leaving only the digits.
See ?gsub for more information.
HTH,
Marc Schwartz
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Re: [R] removing characters from a string
look at "?gsub()", e.g.,
string <- "ab03def10-523rtf"
string
gsub("[^0-9]", "", string)
gsub("[0-9]", "", string)
I hope it helps.
Best,
Dimitris
Dimitris Rizopoulos
Ph.D. Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven
Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/16/336899
Fax: +32/16/337015
Web: http://www.med.kuleuven.ac.be/biostat/
http://www.student.kuleuven.ac.be/~m0390867/dimitris.htm
- Original Message -
From: "Vivek Rao" <[EMAIL PROTECTED]>
To:
Sent: Tuesday, April 12, 2005 2:54 PM
Subject: [R] removing characters from a string
Is there a simple way in R to remove all characters
from a string other than those in a specified set? For
example, I want to keep only the digits 0-9 in a
string.
In general, I have found the string handling abilities
of R a bit limited. (Of course it's great for stats in
general). Is there a good reference on this? Or should
R programmers dump their output to a text file and use
something like Perl or Python for sophisticated text
processing?
I am familiar with the basic functions such as nchar,
substring, as.integer, print, cat, sprintf etc.
__
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http://www.R-project.org/posting-guide.html
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Re: [R] removing characters from a string
On Tuesday 12 April 2005 08:03, Liaw, Andy wrote:
> Just gsub() non-numerics with ""; e.g.:
> > gsub("[a-zA-Z]", "", "aB9c81")
>
> [1] "981"
>
> [I'm really bad in regular expressions, and don't know how to
> construct "non-numerics".]
(So am I, but) perhaps "[^0-9]".
Deepayan
>
> Andy
>
> > From: Vivek Rao
> >
> > Is there a simple way in R to remove all characters
> > from a string other than those in a specified set? For
> > example, I want to keep only the digits 0-9 in a
> > string.
> >
> > In general, I have found the string handling abilities
> > of R a bit limited. (Of course it's great for stats in
> > general). Is there a good reference on this? Or should
> > R programmers dump their output to a text file and use
> > something like Perl or Python for sophisticated text
> > processing?
> >
> > I am familiar with the basic functions such as nchar,
> > substring, as.integer, print, cat, sprintf etc.
> >
> > __
> > R-help@stat.math.ethz.ch mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide!
> > http://www.R-project.org/posting-guide.html
>
> __
> R-help@stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide!
> http://www.R-project.org/posting-guide.html
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Re: [R] abline() with xyplot()
On Tuesday 12 April 2005 07:38, Chloe ARCHINARD wrote:
> Hello all,
> I'm a new user on R, and I used the abline function to draw a line on
> my graph but it doesn't work with xyplot(). With the plot function,
> abline() is ok but with plot it doesn't make what I want. Maybe it's
> a little thing to change in plot() but I don't find what! With xyplot
> I write this :
> Xyplot(m~ordered(l,levels=1),
> type="b",xlab="lagdist",ylab="Moran'I",lty=1,lwd=2,cex=1.5,pch=pch)
> Abline(h=0,lty=2)
I'm not aware of anything called 'Xyplot' or 'Abline' (note that R is
case sensitive).
> There's no error message but no line too.
> If someone see my error or know how to do, thanks in advance.
'xyplot' is part of a graphics system that is different from standard R
graphics. If you want to use it, you first need to learn how.
help(Lattice) has some pointers that should get you started.
In this case, you probably want something like
xyplot(m ~ ordered(l, levels=1),
type="b", xlab="lagdist",
ylab="Moran'I", lty=1, lwd=2,
cex=1.5, pch=pch,
panel = function(...) {
panel.abline(h = 0, lty = 2)
panel.xyplot(...)
})
-Deepayan
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RE: [R] removing characters from a string
Just gsub() non-numerics with ""; e.g.:
> gsub("[a-zA-Z]", "", "aB9c81")
[1] "981"
[I'm really bad in regular expressions, and don't know how to construct
"non-numerics".]
Andy
> From: Vivek Rao
>
> Is there a simple way in R to remove all characters
> from a string other than those in a specified set? For
> example, I want to keep only the digits 0-9 in a
> string.
>
> In general, I have found the string handling abilities
> of R a bit limited. (Of course it's great for stats in
> general). Is there a good reference on this? Or should
> R programmers dump their output to a text file and use
> something like Perl or Python for sophisticated text
> processing?
>
> I am familiar with the basic functions such as nchar,
> substring, as.integer, print, cat, sprintf etc.
>
> __
> R-help@stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide!
> http://www.R-project.org/posting-guide.html
>
>
>
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[R] removing characters from a string
Is there a simple way in R to remove all characters from a string other than those in a specified set? For example, I want to keep only the digits 0-9 in a string. In general, I have found the string handling abilities of R a bit limited. (Of course it's great for stats in general). Is there a good reference on this? Or should R programmers dump their output to a text file and use something like Perl or Python for sophisticated text processing? I am familiar with the basic functions such as nchar, substring, as.integer, print, cat, sprintf etc. __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] abline() with xyplot()
probably you want to look at this: help(panel.abline, package="lattice") I hope it helps. Best, Dimitris Dimitris Rizopoulos Ph.D. Student Biostatistical Centre School of Public Health Catholic University of Leuven Address: Kapucijnenvoer 35, Leuven, Belgium Tel: +32/16/336899 Fax: +32/16/337015 Web: http://www.med.kuleuven.ac.be/biostat/ http://www.student.kuleuven.ac.be/~m0390867/dimitris.htm - Original Message - From: "Chloe ARCHINARD" <[EMAIL PROTECTED]> To: Sent: Tuesday, April 12, 2005 2:38 PM Subject: [R] abline() with xyplot() Hello all, I'm a new user on R, and I used the abline function to draw a line on my graph but it doesn't work with xyplot(). With the plot function, abline() is ok but with plot it doesn't make what I want. Maybe it's a little thing to change in plot() but I don't find what! With xyplot I write this : Xyplot(m~ordered(l,levels=1), type="b",xlab="lagdist",ylab="Moran'I",lty=1,lwd=2,cex=1.5,pch=pch) Abline(h=0,lty=2) There's no error message but no line too. If someone see my error or know how to do, thanks in advance. Chloé Archinard CEFE-CNRS 1919 Route de Mende 34293 Montpellier, Cedex 5, France -- passerelle antivirus du campus CNRS de Montpellier -- [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] abline() with xyplot()
Hello all, I'm a new user on R, and I used the abline function to draw a line on my graph but it doesn't work with xyplot(). With the plot function, abline() is ok but with plot it doesn't make what I want. Maybe it's a little thing to change in plot() but I don't find what! With xyplot I write this : Xyplot(m~ordered(l,levels=1), type="b",xlab="lagdist",ylab="Moran'I",lty=1,lwd=2,cex=1.5,pch=pch) Abline(h=0,lty=2) There's no error message but no line too. If someone see my error or know how to do, thanks in advance. Chloé Archinard CEFE-CNRS 1919 Route de Mende 34293 Montpellier, Cedex 5, France -- passerelle antivirus du campus CNRS de Montpellier -- [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] R as programming language: references?
On Apr 12, 2005 11:54 AM, Duncan Murdoch <[EMAIL PROTECTED]> wrote: > > - Original Message - From: "Federico Calboli" > > <[EMAIL PROTECTED]> > > To: "r-help" > > Sent: Tuesday, April 12, 2005 5:14 PM > > Subject: [R] R as programming language: references? > > > > > >> Hi All, > >> > >> I am looking for references on R as a programming language (apart form > >> the standard R-lang.pdf and the other manuals), reference that would > >> cover _in_depth_ things like loops, code optimisation, debugging tools > >> etc... and is as up-to-date as possible. > >> > >> Can anyone suggest any book or other reference apart from the "green > >> book" and the V&R "S-programming"? > > I think you've already got the best references. There is always the source. In a sense, it IS the most in-depth and up-to-date description of the intricacies of using the language, though it isn't as easy to read as V&R's S Programming. In-depth and up-to-date are tradeoffs rather than being complementary. best, -tony "Commit early,commit often, and commit in a repository from which we can easily roll-back your mistakes" (AJR, 4Jan05). A.J. Rossini [EMAIL PROTECTED] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] persp plot
Dan Gerrard wrote: Is there a way to mark specific tick points on x, y and z axes? Also, I'm trying to overlay a persp plot using the command lines(..) but it doesn't appear to work, does anyone know why? See the examples of ?persp how to add elements to an existing persp() plot, in particular the function trans3d() given in the examples. I'm also trying to rotate the persp plot using rotation but this doesn't work either? I get the error parameter "rotation" couldn't be set in high-level plot() function does anyone know why? Because it does not exist. See ?persp. Uwe Ligges Thanks for any help. Send instant messages to your online friends http://uk.messenger.yahoo.com [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] persp plot
Is there a way to mark specific tick points on x, y and z axes? Also, I'm trying to overlay a persp plot using the command lines(..) but it doesn't appear to work, does anyone know why? I'm also trying to rotate the persp plot using rotation but this doesn't work either? I get the error parameter "rotation" couldn't be set in high-level plot() function does anyone know why? Thanks for any help. Send instant messages to your online friends http://uk.messenger.yahoo.com [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] R as programming language: references?
Feng Chen wrote: > Maybe you can try this: > http://cran.r-project.org/doc/manuals/fullrefman.pdf No, that's just documentation for the standard library functions. > - Original Message - From: "Federico Calboli" > <[EMAIL PROTECTED]> > To: "r-help" > Sent: Tuesday, April 12, 2005 5:14 PM > Subject: [R] R as programming language: references? > > >> Hi All, >> >> I am looking for references on R as a programming language (apart form >> the standard R-lang.pdf and the other manuals), reference that would >> cover _in_depth_ things like loops, code optimisation, debugging tools >> etc... and is as up-to-date as possible. >> >> Can anyone suggest any book or other reference apart from the "green >> book" and the V&R "S-programming"? I think you've already got the best references. Duncan Murdoch __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] R as programming language: references?
On Tue, 2005-04-12 at 17:45 +0800, Feng Chen wrote: > Maybe you can try this: > http://cran.r-project.org/doc/manuals/fullrefman.pdf I was thinking of something that would not limit itself to defining all possible functions and that I do not have already on my HD... F -- Federico C. F. Calboli Department of Epidemiology and Public Health Imperial College, St Mary's Campus Norfolk Place, London W2 1PG Tel +44 (0)20 7594 1602 Fax (+44) 020 7594 3193 f.calboli [.a.t] imperial.ac.uk f.calboli [.a.t] gmail.com __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] R as programming language: references?
Maybe you can try this: http://cran.r-project.org/doc/manuals/fullrefman.pdf - Original Message - From: "Federico Calboli" <[EMAIL PROTECTED]> To: "r-help" Sent: Tuesday, April 12, 2005 5:14 PM Subject: [R] R as programming language: references? Hi All, I am looking for references on R as a programming language (apart form the standard R-lang.pdf and the other manuals), reference that would cover _in_depth_ things like loops, code optimisation, debugging tools etc... and is as up-to-date as possible. Can anyone suggest any book or other reference apart from the "green book" and the V&R "S-programming"? Cheers, Federico Calboli -- Federico C. F. Calboli Department of Epidemiology and Public Health Imperial College, St Mary's Campus Norfolk Place, London W2 1PG Tel +44 (0)20 7594 1602 Fax (+44) 020 7594 3193 f.calboli [.a.t] imperial.ac.uk f.calboli [.a.t] gmail.com __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] R as programming language: references?
Hi All, I am looking for references on R as a programming language (apart form the standard R-lang.pdf and the other manuals), reference that would cover _in_depth_ things like loops, code optimisation, debugging tools etc... and is as up-to-date as possible. Can anyone suggest any book or other reference apart from the "green book" and the V&R "S-programming"? Cheers, Federico Calboli -- Federico C. F. Calboli Department of Epidemiology and Public Health Imperial College, St Mary's Campus Norfolk Place, London W2 1PG Tel +44 (0)20 7594 1602 Fax (+44) 020 7594 3193 f.calboli [.a.t] imperial.ac.uk f.calboli [.a.t] gmail.com __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] TSeries GARCH Estimates accuracy
GARCH models are notoriously hard to optimize, so I'm not terribly surprised. The first thing is to make sure that your reference results are really better than what you are getting in R. Perhaps they have improved it, but the last time I looked at garch in S-PLUS, it did not necessarily give good results. I don't know anything about the SAS routine. The first-aid approach to getting better estimates is to start the optimization at various locations and pick the best one you get. One starting point might be near to (.05, .9) -- that is, .9 times the lagging conditional variance. Another would be to restart from where the routine ended. From the help file for 'garch' it says that the default starting point is with values close to zero -- that is not a very good starting point. A more involved approach would be to change the routine so that the intercept is derived from the desired asymptotic variance (usually the unconditional variance) and the other parameter estimates. Optimizers tend to be much happier with this problem. The R-sig-finance list is a more likely spot for a discussion like this. Patrick Burns Burns Statistics [EMAIL PROTECTED] +44 (0)20 8525 0696 http://www.burns-stat.com (home of S Poetry and "A Guide for the Unwilling S User") Sanjay Kumar Singh wrote: Hi, I am trying to fit a GARCH(1,1) model to a financial timeseries using the 'garch' function in the tseries package. However the parameter estimates obtained sometimes match with those obtained using SAS or S-Plus (Finmetrics) and sometimes show a completely different result. I understand that this could be due to the way optimization of MLEs are done, however, I would appreciate any help to obtain consistent results using R. Also is there any garch simulation function available other than garchSim from fseries package? Thanks in advance, Sanjay __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] install own packages
Christian Hoffmann wrote: Hi, Soory, if I missed relevant help pages. Yes, you missed quite a lot - the "R Installation and Administration" manual - the help ?install.packages which points you to - ?INSTALL - and there's also an article on package management in the R Help Desk of R-News 3/3 Uwe Ligges I have developed several packages myself and want to give them to a collegue in *.tar.gz form (Unix, Solaris). What is the proper function to install them? install.packages() with a path pointing to the local temp instead of to CRAN? > Thanks for help. Christian __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] R Package: mmlcr and/or flexmix
> On Tue, 12 Apr 2005 00:44:17 -0400, > Geller, Scott (IHG) (GS() wrote: > Greetings > I'm a relatively new R user and I'm trying to build a latent class model. > I've used the 'R Site Search' and it appears there's not much dialogue on > these packages [...] > libray(flexmix) > m1<-flexmix(nts ~ first_brand_HOLIDAY+ perc_zone1+ perc_Group_nights+ > perc_num_asian+ DaysBetweenStays+ CROStays+ DaysSinceLastStay+ > wghtmean_median_age_pop100+ perc_num_white+ perc_num_hispanic+ > perc_CROStays+ numMonthsActive+ WEBStays+ property_loyalty+ perc_NoZone+ > rho+ PCR_Dummy_class+ ltgold1+ ltgold3+ p_hat_PCR, data = data, k = 2, model > = FLXglm(family = "poisson")) > rm1<-refit(m1) > summary(rm1) [ Scott sent me in private a subset of the data ] For me this seems to work fine: R> set.seed(123) R> m1<-flexmix(nts ~ first_brand_HOLIDAY+ perc_zone1+ perc_Group_nights+ + perc_num_asian+ DaysBetweenStays+ CROStays+ DaysSinceLastStay+ + wghtmean_median_age_pop100+ perc_num_white+ perc_num_hispanic+ + perc_CROStays+ numMonthsActive+ WEBStays+ property_loyalty+ perc_NoZone+ + rho+ PCR_Dummy_class+ ltgold1+ ltgold3+ p_hat_PCR, data = data, k = 2, model + = FLXglm(family = "poisson")) R> m1 Call: flexmix(formula = nts ~ first_brand_HOLIDAY + perc_zone1 + perc_Group_nights + perc_num_asian + DaysBetweenStays + CROStays + DaysSinceLastStay + wghtmean_median_age_pop100 + perc_num_white + perc_num_hispanic + perc_CROStays + numMonthsActive + WEBStays + property_loyalty + perc_NoZone + rho + PCR_Dummy_class + ltgold1 + ltgold3 + p_hat_PCR, data = data, k = 2, model = FLXglm(family = "poisson")) Cluster sizes: 1 2 93 906 convergence after 49 iterations R> rm1<-refit(m1) R> R> summary(rm1) Call: refit(m1) Component 1 : Estimate Std. Error z value Pr(>|z|) (Intercept) 1.0108e+00 6.4399e-01 1.5696 0.1164971 first_brand_HOLIDAY-9.3504e-01 4.6151e-01 -2.0261 0.0427594 perc_zone1 1.3936e-01 7.4383e-01 0.1874 0.8513845 ... - Component 2 : Estimate Std. Error z value Pr(>|z|) (Intercept) 1.00799714 0.39133294 2.5758 0.01000 first_brand_HOLIDAY-0.07928984 0.15935997 -0.4976 0.61880 perc_zone1 0.01208886 0.42596711 0.0284 0.97736 ... So I cannot reproduce the problem. Is maybo one cluster in your solution empty? The EM algorithm can end up in a local optimum with one cluster empty ... either run flexmix() several times by hand or use stepFlexmix() to do so automatically. HTH, -- --- Friedrich Leisch Institut für Statistik Tel: (+43 1) 58801 10715 Technische Universität WienFax: (+43 1) 58801 10798 Wiedner Hauptstraße 8-10/1071 A-1040 Wien, Austria http://www.ci.tuwien.ac.at/~leisch __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
