Peter and Po Su, thanks.
For those who haven't read it, it attempts
three things:
* provide an overview of the world of R
(from the point of view of an R session)
* tell of ways to find objects and information
* push you towards organizing your attack
on a problem
Pat
On 27/08/2014 14:03, p
Hi Aseem:
I will try to keep this as short as possible, because a lot of the issue here
is more with understanding netcdf file structure than with R, because once you
understand the former using ncdf4 is pretty straightforward.. So if you want a
more detailed response we should probably take i
On Thu, Aug 28, 2014 at 3:36 AM, eguichard wrote:
> Thank you.
> I can improve my program with your response but I have an other problem.
>
> /double essai (double *Px, int *tailleP)
> {
> int i;
> for (i = 0; i < *tailleP; i++)
> {
> Px[i]=Px[i]*2;
>
Not an R question, so off topic here. But I think this is what they
invented wikipedia for: see
http://en.wikipedia.org/wiki/Comparison_of_spreadsheet_software
Best,
Ista
On Wed, Aug 27, 2014 at 7:01 PM, Grant Rettke wrote:
> Good evening,
>
> Suppose that /the business/ want to store tabular da
Please stop posting on this plain text list using HTML. You are not a freshman
any more.
Is anyone really considering the use of a word processor (equivalent to MS
Word) for managing this tabular data?
The usual quick-and-dirty solution typically involves a spreadsheet program,
but they are so
Hello
I have an experiment with two factors MANAGEMENT and REGION. And I have three
MANAGEMENT types and three REGIONS. Like this.
REGION: A, B and C
MANAGEMENT: N, P, ST
the independent variable is called PHt
I have set the aov in R in two possible ways. The first model I understand, but
I do
Hi,
Yes this is the canadian domain data.
I want to extract only for parts of western Canada.
Further, this data has three variable namely pr, tmax and tmin. I am trying
to extract three different .nc files of each parameters for a smaller
domain.
below is the results of str(myfile).
> str(ncold)
L
Thanks David. It turns out that I was in fact using a custom index.perm,
but not on purpose. What happened was I used the "[" method on the
trellis object ( lattice:::`[.trellis`), which of course is nothing but
a short-cut for updating the index.perm. Lesson learned...
Regards,
Ben
On 08/27/2014
Good evening,
Suppose that /the business/ want to store tabular data inside of a
file. They want manage that file using a GUI program that runs on OSX,
Linux, and Windows. Additionally, it needs to be OSS and *not* MS Word.
Two options that immediately come to mind are [LibreOffice] and
[OpenOff
Dear Chad,
It's possible that I don't understand properly what you've done, but it appears
as if you're passing to bootSem() the covariance matrices for the observed data
rather than the case-by-variable data sets themselves. That's also what you say
you're doing, and it's what the error messag
Dear Ranjan,
thanks, that was what I was looking for. Somehow my 'grep' must have
missed that.
Cheers,
Marius
On Wed, Aug 27, 2014 at 8:34 AM, Marius Hofert
wrote:
> Dear Sarah, Dear David,
>
> thanks for helping. I know the FAQ and I know the R News article, but
> I still couldn't figure it
David,
you caught my typo of excess quotation marks. this should work
ranEff1 <- ~Variety -1
random=list(Block=get(BlockFunction)(ranEff1)))
On Wed, Aug 27, 2014 at 4:41 PM, David Winsemius wrote:
>
> On Aug 27, 2014, at 1:33 PM, Richard M. Heiberger wrote:
>
>> do you have control over the ex
I missed this question.
1. For survreg.
help("predict.survreg") shows an example of drawing a survival curve
Adding a survfit method has been on my list for a long time, since it would make this
information easier to find.
2. intcox. I had not been familiar with this function. Even thoug
On Aug 27, 2014, at 1:33 PM, Richard M. Heiberger wrote:
> do you have control over the external source?
>
> if so, then something like
>
> BlockFunction <- "pdComSymm"
> ranEff1 <- "~Variety -1"
I doubt that would work, since it is not a formula object.
>
> fm <- lme(yield ~ nitro, data=Oats
do you have control over the external source?
if so, then something like
BlockFunction <- "pdComSymm"
ranEff1 <- "~Variety -1"
fm <- lme(yield ~ nitro, data=Oats,
random=list(Block=get(BlockFunction)(ranEff1)))
The above is untested. An example if get() is
> get("sum")(1:4)
[1] 10
The main pr
Sorry for the misspelling! And more importantly, thanks a lot for the
nice solution and for the quick help!
On Wed, Aug 27, 2014 at 4:22 PM, David Winsemius wrote:
>
> On Aug 27, 2014, at 1:11 PM, Gang Chen wrote:
>
>> Good point!
>>
>> Here is an example:
>>
>> library(nlme)
>> fm <- lme(yield ~
On Aug 27, 2014, at 1:11 PM, Gang Chen wrote:
> Good point!
>
> Here is an example:
>
> library(nlme)
> fm <- lme(yield ~ nitro, data=Oats, random=list(Block=pdComSymm(~Variety-1)))
>
One problem is that youa re misspelling the function name.
> Now the problem I'm facing is that the followi
Good point!
Here is an example:
library(nlme)
fm <- lme(yield ~ nitro, data=Oats, random=list(Block=pdComSymm(~Variety-1)))
Now the problem I'm facing is that the following part
pdComSymm(~Variety-1)
is read in as a string of characters from an external source:
ranEff <- 'pdComSymm(~Variety-1
Dear All
please provide insights to the following, if possible:
we have
E <-c(8.2638 ,7.9634, 7.5636, 6.8669, 5.7599, 8.1890, 8.2960, 8.1481, 8.1371,
8.1322 ,7.9488, 7.8416, 8.0650,
8.1753, 8.0986 ,8.0224, 8.0942, 8.0357, 7.8794, 7.8691, 8.0660, 8.0753,
8.0447, 7.8647, 7.8837, 7.8416,
7.6967
On Aug 27, 2014, at 12:44 PM, Gang Chen wrote:
> Thanks for the help! However, I just need to get
>
> pdCompSymm(~1 + Age)
That's not a formula in the R sense of the word. You should do a better job of
posting a use case. Perhaps you want an expression?
--
David.
>
> without a tilde (~) at
Thanks for the help! However, I just need to get
pdCompSymm(~1 + Age)
without a tilde (~) at the beginning.
On Wed, Aug 27, 2014 at 3:34 PM, David Winsemius wrote:
>
> On Aug 27, 2014, at 11:19 AM, Gang Chen wrote:
>
>> A random effect formulation for R package nlme is read in as a string
>> of
Hello,
I am having difficulty resolving an error I receive trying to bootstrap a
multigroup SEM. The error (below) indicates that the model called to
bootSem doesn't contain matrices. This is true, sort of, because I created
a list of two covariance matrices for the model to call. All of this synt
Thank you.
I can improve my program with your response but I have an other problem.
/double essai (double *Px, int *tailleP)
{
int i;
for (i = 0; i < *tailleP; i++)
{
Px[i]=Px[i]*2;
Rprintf ("I print Px %f\t", Px[i]);
}
Rpri
On Aug 27, 2014, at 11:19 AM, Gang Chen wrote:
> A random effect formulation for R package nlme is read in as a string
> of characters from an input file:
>
> ranEff <- "pdCompSymm(~1+Age)"
>
> I need to convert 'ranEff' to a formula class. However, as shown below:
>
>> as.formula(ranEff)
> ~1
A random effect formulation for R package nlme is read in as a string
of characters from an input file:
ranEff <- "pdCompSymm(~1+Age)"
I need to convert 'ranEff' to a formula class. However, as shown below:
> as.formula(ranEff)
~1 + Age
the "pdCompSymm" is lost in the conversion. Any solutions?
On Aug 27, 2014, at 2:18 AM, Ingo Wardinski wrote:
> Hello,
> I try to plot w-correlation matrix of singular spectrum analysis by using the
> package Rssa. This is an example:
> > library(Rssa)
> > s <- ssa(co2)
> > w <- wcor(s, groups = 1:20)
> > plot(w,cex.label=3),scales=list(at=c(10,20,30,40
Hi,
I have not followed the e-mail trail, but if you are looking for the C
source code for pbinom, then it is pbinom.c in src/nmath.
HTH,
Ranjan
On Wed, 27 Aug 2014 08:34:11 -0400 Marius Hofert
wrote:
> Dear Sarah, Dear David,
>
> thanks for helping. I know the FAQ and I know the R News arti
Thank you very much for your quick reply Wolfgang. The 0 does make sense - I'm
working on some behavioural data and in one study none reported that particular
behaviour. Up til now I have been calculating I2 without that study, as it's on
the small side I don't think it makes much difference. I'
The warning message pretty much says it: When one of the variances is zero,
then the I^2 statistic (and various other things) cannot be computed, at least
if one sticks to the usual equations/methods. So, if you think the 0 sampling
variances really make sense and you really want to get somethin
Dear Sarah, Dear David,
thanks for helping. I know the FAQ and I know the R News article, but
I still couldn't figure it out. First, pbinom calls
.External(C_pbinom,...). Grepping for C_pbinom reveals... nothing
(except the appearance in .External). Going to ./src/main/names.c
reveals "{"pbinom",
Hi Luigi,
See in line.
On Wed, Aug 27, 2014 at 9:42 AM, Luigi Marongiu
wrote:
> Dear all,
> I would like to ask whether is possible to draw a scatterplot using
> the simple plot() function when the data is factorial. Without the
> addition of the argument factor(), plot() represent the factorial
With lattice graphics, yes
libary(lattice)
xyplot(y ~ z, data=my.data)
bwplot(y ~ z, data=my.data)
stripplot(y ~ z, data=my.data)
With base graphics, probably not.
More importantly, don't use attach. It will get you into trouble.
In this case, it didn't work for me because I had a variable name
It is, but stripchart() is simpler.
plot(y~as.numeric(z), my.data, xlab="x", xaxt="n", pch=19)
axis(1, 1:4, LETTERS[1:4])
If you want more spacing along the x-axis try
plot(y~as.numeric(z), my.data, xlab="x", xaxt="n",
xlim=c(.5, 4.5), pch=19)
axis(1, 1:4, LETTERS[1:4])
---
Dear all,
I would like to ask whether is possible to draw a scatterplot using
the simple plot() function when the data is factorial. Without the
addition of the argument factor(), plot() represent the factorial data
on a linear scale whereas using this argument transforms plot() from a
scatterplot
C'mon! Already now, Google gives a handful of links to Twitter or R-help or
r-bloggers or other places that talk _about_ the write-up.
It's
http://www.burns-stat.com/r-navigation-tools
-pd
On 27 Aug 2014, at 09:01 , PO SU wrote:
>
> I think the article from burns-stat is very worth reading
On Wed, Aug 27, 2014 at 4:58 AM, eguichard wrote:
> Hi everybody,
> I am including some C code in R program using the .C interface.
> I would like use a C subfunction calling by C void function.
>
> /double essai (double Px[], int tailleP)
> {
> Rprintf ("I print Px %d\t", Px[1]);
>
Hi
Please be more specific and try to post some example to simplify elaborating
answer.
How big is your matrix. Double loop seems to be the first which come to my mind
however it can be unpractical when dealing with big matrix or if you want to do
this task repeatedly.
Petr
> -Original
Dear anna,
Unless the original matrix has a massive number of columns, why not just use
loops? R programmers often have an unnecessary phobia of loops, and will puzzle
over a programming problem for hours that can be solved by loops in seconds.
You don't say what specifically you want to do, bu
Hi, I'm doing a meta-analysis in metafor. All is fine except when there are 0s
in the values that i'm pooling, then i get a pooled estimate but not the I2
that i am also interested in.
for example:
summary(rma.1<-rma(yi,vi,data=mix,method="ML",knha=F,weighted=F,intercept=T))
(where yi are the st
R FAQ 7.40
http://cran.r-project.org/doc/FAQ/R-FAQ.html#How-do-I-access-the-source-code-for-a-function_003f
Sarah
On Tuesday, August 26, 2014, Marius Hofert
wrote:
> Dear expeRts,
>
> I would like to find out how R computes pbinom(). A grep in the
> source code reveiled src/library/stats/R/dis
Hi everybody,
I am including some C code in R program using the .C interface.
I would like use a C subfunction calling by C void function.
/double essai (double Px[], int tailleP)
{
Rprintf ("I print Px %d\t", Px[1]);
return 57;
}
void test_essai (double *Px, int *tailleP, double
On 08/27/2014 11:18 AM, Ingo Wardinski wrote:
Hello,
I try to plot w-correlation matrix of singular spectrum analysis by
using the package Rssa. This is an example:
> library(Rssa)
> s <- ssa(co2)
> w <- wcor(s, groups = 1:20)
> plot(w,cex.label=3),scales=list(at=c(10,20,30,40)))
I was wron
Hello,
I try to plot w-correlation matrix of singular spectrum analysis by
using the package Rssa. This is an example:
> library(Rssa)
> s <- ssa(co2)
> w <- wcor(s, groups = 1:20)
> plot(w,cex.label=3),scales=list(at=c(10,20,30,40)))
However cex.label dos not have any effect. Also I would like
On Aug 26, 2014, at 8:14 PM, Marius Hofert wrote:
Dear expeRts,
I would like to find out how R computes pbinom(). A grep in the
source code reveiled src/library/stats/R/distn.R:146:
.External(C_pbinom, q, size, prob, lower.tail, log.p), so
'C_pbinom' refers to compiled C/C++ code loaded into R
I think the article from burns-stat is very worth reading , You can google it
,and hope you find it useful.
--
PO SU
mail: desolato...@163.com
Majored in Statistics from SJTU
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