Dear R community,
I have the following problem, and kindly ask for some support.
I want to create a network object, representing a directed network on basis of
an edgelist. The first column contains some unique ID of project leaders, the
second project partners, let's say:
x <- cbind(rbind(1,1
I found that if I comment out the matplot function within the choicemodelr
function (i.e. remove plotting from within the choicemodelr function while
it is running), then ChoiceModelR does not slow down during estimation.
So, there must be an issue with the plotting from within a function while
it
hello,
please advice what is wrong at the below syntax:
"Trial<-read.table("Trial.txt",header=TRUE)
Trial
save.image(file="Trial.RData")
data(Trial)
fit<-logistf(data=Trial, y~x1+x2)
"
and here is the error I get:
"Warning message:
In data(Trial) : data set Trial not found
"
regards,
yasmin
I run the following:
library(actuar)
x <- seq(0, 22, 0.5)
fl <- discretize(plnorm(x, 2.1), from = 0, to = 22, step = 0.5, method
="lower")
Fs <- aggregateDist("recursive", model.freq = "poisson",model.sev = fl,
lambda = 10, x.scale = 0.5)
Warning message:
In panjer(fx = model.sev, dist = dist, p0 =
Hello everyone,
i found that both of the 2 functions ("expand.grid" and "data.frame") can
be used to produce data frame. are there any difference between them?
thanks for your help!
zhaoran
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R-help@r-pro
There were some issues with the CRAN submission and I was confused about
the earlier package availability. It is available now in source form (
http://cran.r-project.org/web/packages/FField/index.html)
The sequence for the demo of label repulsion:
install.packages("FField", type = "source")
libr
Dear List members,
I would like to use the Kalman-filter program for forecasting - namely for
postprocessing numerical model results of 2m temperature. I have looked through
the help of the Kalman-filtering programs, mainly the KalmanForecast and I have
read about the newer packages like KFAS
Mike,
Do something like:
require(rms)
dd <- datadist(mydatarame); options(datadist='dd')
f <- Rq(y ~ rcs(age,4)*sex, tau=.5) # use rq function in quantreg
summary(f) # inter-quartile-range differences in medians of y (b/c tau=.5)
plot(Predict(f, age, sex)) # show age effect on median as a co
I just realized this was also possible:
> assign('TRUE', FALSE)
> TRUE
[1] TRUE
> get('TRUE')
[1] FALSE
but it is probably a different story.
Regards,
Yihui
--
Yihui Xie
Phone: 206-667-4385 Web: http://yihui.name
Fred Hutchinson Cancer Research Center, Seattle
On Fri, Jun 28, 2013 at 6:30 PM,
On 29/06/13 02:54, John Fox wrote:
Dear Duncan and Steve,
Since Steve's example raises it, I've never understood why it's legal to
change the built-in global "constants" in R, including T and F. That just
seems to me to set a trap for users. Why not treat these as reserved
symbols, like TRUE, In
And there is no real magic in which(). You already know that
V[I]
where 'I' is a logical vector the length of 'V' extracts the values
in 'V' corresponding to the TRUE's in 'I'. Replace 'V' with the vector
made by seq_along(I), (== 1, 2, ..., length(I)), and you have the
essentials of which(I).
?which
-- Bert
On Fri, Jun 28, 2013 at 2:58 PM, Julio Sergio wrote:
> One of the techniques to subset, a vector for instance, is the following:
>
> V <- c(18, 8, 5, 41, 8, 7)
> V
> ## [1] 18 8 5 41 8 7
> ( I <- abs(V - 9) <= 3 )
> ## [1] FALSE TRUE FALSE FALSE TRUE TRUE
> V[I]
On Jun 28, 2013, at 23:58 , Julio Sergio wrote:
> One of the techniques to subset, a vector for instance, is the following:
>
> V <- c(18, 8, 5, 41, 8, 7)
> V
> ## [1] 18 8 5 41 8 7
> ( I <- abs(V - 9) <= 3 )
> ## [1] FALSE TRUE FALSE FALSE TRUE TRUE
> V[I]
> ## [1] 8 8 7
>
> Howe
One of the techniques to subset, a vector for instance, is the following:
V <- c(18, 8, 5, 41, 8, 7)
V
## [1] 18 8 5 41 8 7
( I <- abs(V - 9) <= 3 )
## [1] FALSE TRUE FALSE FALSE TRUE TRUE
V[I]
## [1] 8 8 7
However, sometimes we are interested in the indexes of the elements w
Thanks for the workaround and the explanation
Alain
De : Milan Bouchet-Valat [nalimi...@club.fr]
Date d'envoi : vendredi 28 juin 2013 19:20
À : LE TERTRE Alain
Cc : 'R-help@r-project.org'
Objet : Re: [R] use of formula in survey analysis with replicated wei
On 6/27/2013 12:34 AM, Suparna Mitra wrote:
> Hello R experts,
>I am having a problem to edit legend in ggplot using four variables.
>
> My data structure is :
> str(df)
> 'data.frame': 10 obs. of 6 variables:
> $ id: Factor w/ 2 levels "639A","640": 1 1 1 1 1 2
> 2 2
Le vendredi 28 juin 2013 à 17:44 +0200, LE TERTRE Alain a écrit :
> Hi there,
> I would like to use a formula inside a call to withReplicates in a survey
> analysis.
> If the initial call with formula expressed inside the function works as
> expected, defining the formula outside gives an error m
Dear R group:
I just bought a Haswell i7-4770k machine, so I went through the
trouble of creating a small website with some comparative benchmarks.
I also made it easy for others to contribute benchmarks. if you are
interested, it's all at http://R.ivo-welch.info/ . enjoy.
/iaw
Ivo Welch (
Dear Brian,
> -Original Message-
> From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
> project.org] On Behalf Of Prof Brian Ripley
> Sent: Friday, June 28, 2013 11:16 AM
> To: r-help@r-project.org
> Subject: Re: [R] Lexical scoping is not what I expect
>
> On 28/06/2013 15:54,
Hi there,
I would like to use a formula inside a call to withReplicates in a survey
analysis.
If the initial call with formula expressed inside the function works as
expected, defining the formula outside gives an error message.
See example below, adapted from survey:withReplicates help page.
li
Dear Duncan,
I think that it's reasonable to make a distinction between symbols
representing functions and those representing built-in constants, even if,
as in the case of pi and T (and letters, etc.), the latter are technically
implemented as variables.
Although it may be natural to use the va
Your comments #2 and 3 are correct.
The closing brace is missing and. Normally the end of the pr after the
instruction
For the comment #1 relate to the declaration img, I don't know if there is
another way to import data from fortran in R.
Armel
-Original Message-
From: Duncan Murdoch
On 28/06/2013 15:54, John Fox wrote:
Dear Duncan and Steve,
Since Steve's example raises it, I've never understood why it's legal to
change the built-in global "constants" in R, including T and F. That just
seems to me to set a trap for users. Why not treat these as reserved
symbols, like TRUE,
On 28/06/2013 10:54 AM, John Fox wrote:
Dear Duncan and Steve,
Since Steve's example raises it, I've never understood why it's legal to
change the built-in global "constants" in R, including T and F. That just
seems to me to set a trap for users. Why not treat these as reserved
symbols, like TRU
Dear Duncan and Steve,
Since Steve's example raises it, I've never understood why it's legal to
change the built-in global "constants" in R, including T and F. That just
seems to me to set a trap for users. Why not treat these as reserved
symbols, like TRUE, Inf, etc.?
Best,
John
> -Origina
On 28/06/2013 10:46 AM, Kaptue Tchuente, Armel wrote:
Please could you explain what you mean by several typos in my code?
1. img is passed as an argument, but never used.
2. There is no closing brace on the function body.
3. You set the dimension to n*m, when I believe you wanted c(n, m).
Dun
Please could you explain what you mean by several typos in my code?
Anyway, it works very well and keep in minds that here I just wrote a very
simple code to illustrate what I really want since in the reality, the program
is more complex than what you see.
May be I'm wrong but I also prefer to c
On 28/06/2013 10:18 AM, Kaptue Tchuente, Armel wrote:
@ Duncan, I have already used the syntax that you proposed before asking for
help by writing something like
> read_ts<-function(n,m,img) {
> out<-.Fortran("read_ts",
>as.integer(n),
>as.integer(m),
>
@ Duncan, I have already used the syntax that you proposed before asking for
help by writing something like
> read_ts<-function(n,m,img) {
> out<-.Fortran("read_ts",
>as.integer(n),
>as.integer(m),
>img=as.single(rnorm(n*m)))
> return(out$img)
> al
You need to learn to execute one statement at a time in order to debug this
yourself. Copy and paste is your friend. Hint: I already told you that the data
function is inappropriate if the data does not come from a package.
You should be learning to use the str(), head(), and ls() functions to e
HI,
May be this helps:
dat1<- read.table(text="
date1 time date timeSec topic pupilId correct
02/01/2013 14:58 02/01/2013 140323 fdp.fdp 40 TRUE
02/01/2013 14:59 02/01/2013 140372 fdp.fdp 150 TRUE
03/01/2013 11:23 03/01/2013 213833 fdp.percentage_calc_foundation 15 TRUE
03/0
On 28/06/2013 9:28 AM, S Ellison wrote:
> > I too find R's lexical scoping rules straightforward.
> > However, I'd say that if your code relies on lexical
> > scoping to find something, you should probably rewrite your code.
>
> Except of course that almost every function relies on lexical
> s
> > I too find R's lexical scoping rules straightforward.
> > However, I'd say that if your code relies on lexical
> > scoping to find something, you should probably rewrite your code.
>
> Except of course that almost every function relies on lexical
> scoping to some extent!
This could get m
I have encountered what looks to be a problem with ggpairs in ggally. No idea
it is from 3.0 as I had never used ggpairs before update to 3.0 but it sounds a
bit similar
http://support.rstudio.org/help/discussions/problems/6796-ggpairs-in-ggally-very-slow-in-rstudio-and-may-cause-a-crash
John Ka
On 27/06/2013 11:38 PM, David Winsemius wrote:
On Jun 27, 2013, at 8:04 PM, Kaptue Tchuente, Armel wrote:
> Hi there,
>
> I would like to know how to change the line "img=as.single(rnorm(m)))" such
that instead of being a vector of length m as it is now, img is an array of dimension
c=(n,m,o)
Dear R-studio and R colleagues,
I've interacted with the authors of the package "ChoiceModelR" and it looks
like there is a problem in the way RStudio interacts with R3.0.
At least the package ChoiceModelR works just fine under both R gui and
Rstudio when R version is < 3.0
When R3.0 is tested -
http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example
While the str() data is useful it is much better to provide real sample data.
Use dput() to supply it.
If it is a large file send a sample head(dput(df, "somenumber)) with
somenumber just enough to provide
HI,
According to ?t.test() documentation
If ‘paired’ is ‘TRUE’ then both ‘x’ and ‘y’ must be specified and
they must be the same length. Missing values are silently removed
(in pairs if ‘paired’ is ‘TRUE’)
#Example with missing values
set.seed(24)
dat1<- as.data.frame(matrix(sample(c(NA
Thank you very much for your help !
--
View this message in context:
http://r.789695.n4.nabble.com/Scatter-plot-with-error-bars-tp4670502p4670530.html
Sent from the R help mailing list archive at Nabble.com.
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Hi,
set.seed(45)
testframe <- data.frame(a=rnorm(100), b = rnorm(100))
indices <- rep(c(1,2), each = 50)
library(plyr)
ddply(testframe,.(indices),summarize, Cor1=cor(a,b))
# indices Cor1
#1 1 0.002770524
#2 2 -0.10173
A.K.
- Original Message -
From: J
Thanks a lot to everybody who responded! My solution now looks similar
to Ruis and Davids suggestions.
Jannis
On 28.06.2013 11:00, Rui Barradas wrote:
Hello,
You can solve your problem using only base R, with no need for an
external package. The two instrucitons below are two ways of doing
Hello,
You can solve your problem using only base R, with no need for an
external package. The two instrucitons below are two ways of doing the same.
sapply(split(testframe, indices), function(x) cor(x[, 1], x[, 2]))
as.vector(by(testframe, indices, function(x) cor(x[, 1], x[, 2])))
Hope
Yes, I had a look at that function. From the documentation, however, it
did not get clear to me how to split the dataframe into subsets of rows
based on an index argument. Like:
testframe <- data.frame(a=rnorm(100), b = rnorm(100))
indices <- rep(c(1,2), each = 50)
results <- ddply(.dat
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