[R] Add constraints to rbinom
Hi:
I am trying to generate Beta-Binomial random variables and then
calculate Binomial exact confidence intervals to the rate..I was
wondering if I needed to add a constraint such that x=n to it, how do
I go about it. The reason is I am getting data where xn which is
giving a rate1. Heres my code:
set.seed(111)
k-63
x-NULL
p-rbeta(k,3,3)# so that the mean nausea rate is alpha/(alpha+beta)
min-10
max-60
n-as.integer(runif(k,min,max))
for(i in 1:k)
x-cbind(x,rbinom(300,n,p[i]))
x-t(x)
rate-t(t(x)/n)
se_rate-sqrt(rate*(1-rate)/n)
# Exact Confidence Interval
l_cl_exact-qbeta(.025,x,n-x+1)
u_cl_exact-qbeta(.975,x+1,n-x)
for (i in 1:63){
for (j in 1:300)
{
if (x[i,j]==0)
{
l_cl_exact[i,j]-0
u_cl_exact[i,j]-u_cl_exact[i,j]
}
else if (x[i,j]==n[i])
{
l_cl_exact[i,j]-l_cl_exact[i,j]
u_cl_exact[i,j]-1
}
else
l_cl_exact[i,j]-l_cl_exact[i,j]
u_cl_exact[i,j]-u_cl_exact[i,j]
#print(c(i,j))
}
}
Really appreciate any help.
Thanks
Anamika
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Re: [R] Scatter plot with error bars
Are you sure, you want to calculate 68% confidence intervals? Use the add-argument in ?errorbar to add to the previous plot. errbar(x2,y2,y2+1.96*SD2, y2-1.96*SD2, col=green,pch=19, add=TRUE) Best, Nello -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of beginner Sent: Freitag, 28. Juni 2013 02:24 To: r-help@r-project.org Subject: [R] Scatter plot with error bars Hi I would like to plot multiple data sets on a scatter plot with error bars. To do this I write the following code: install.packages(Hmisc) library(Hmisc) x1-data1[,1] y1-data1[,2] x2-data2[,1] y2-data2[,2] x3-data3[,1] y3-data3[,2] SD1-data1[,3] SD2-data2[,3] SD3-data3[,4] delta-runif(5) errbar(x1,y1,y1+SD1, y1-SD1, col=red,pch=19) lines(x1,y1,col=red, pch=19, lty=3) errbar(x2,y2,y2+SD2, y2-SD2, col=green,pch=19) lines(x2,y2,col=green, pch=19, lty=3) errbar(x3,y3,y3+SD3, y3-SD3, col=blue,pch=19) lines(x3,y3,col=blue, pch=19, lty=3) However, with this code I can obtain only the scatter plot for x1, y1, but not for the other data sets. Could you please let me know how should I modify the code presented above ? In other situations, when I try to make a scatter plot of several data sets without error bars, I usually use points () function. However it does not work in the presented case... I would be very grateful for your help. -- View this message in context: http://r.789695.n4.nabble.com/Scatter-plot-with-error-bars-tp4670502.htm l Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] multivariate version of aggregate
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(.data = testframe, INDICES= indices, .fun = function(x) corr(x[,1], x[,2])) Where the last command would yield the correlations between column 1 and 2 of the first 50 and of the last 50 values. Any ideas? Jannis On 27.06.2013 21:43, Greg Snow wrote: Look at the plyr package, probably the ddply function in that package. You can write your own function to do whatever you want on the pieces of the split apart object. Correlation between a specified pair of columns would be simple. On Thu, Jun 27, 2013 at 11:26 AM, Jannis bt_jan...@yahoo.de wrote: Dear List members, i am seeking a multivariate version of aggregate. I want to compute, fro example the correlation between subsets of two vectors. In aggregate, i can only supply one vector with indices for subsets. Is there ready function for this or do i need to program my own? Cheers Jannis __** R-help@r-project.org mailing list https://stat.ethz.ch/mailman/**listinfo/r-helphttps://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/** posting-guide.html http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] multivariate version of aggregate
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 this helps, Rui Barradas Em 28-06-2013 09:31, Jannis escreveu: 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(.data = testframe, INDICES= indices, .fun = function(x) corr(x[,1], x[,2])) Where the last command would yield the correlations between column 1 and 2 of the first 50 and of the last 50 values. Any ideas? Jannis On 27.06.2013 21:43, Greg Snow wrote: Look at the plyr package, probably the ddply function in that package. You can write your own function to do whatever you want on the pieces of the split apart object. Correlation between a specified pair of columns would be simple. On Thu, Jun 27, 2013 at 11:26 AM, Jannis bt_jan...@yahoo.de wrote: Dear List members, i am seeking a multivariate version of aggregate. I want to compute, fro example the correlation between subsets of two vectors. In aggregate, i can only supply one vector with indices for subsets. Is there ready function for this or do i need to program my own? Cheers Jannis __** R-help@r-project.org mailing list https://stat.ethz.ch/mailman/**listinfo/r-helphttps://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/** posting-guide.html http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] multivariate version of aggregate
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 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 this helps, Rui Barradas Em 28-06-2013 09:31, Jannis escreveu: 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(.data = testframe, INDICES= indices, .fun = function(x) corr(x[,1], x[,2])) Where the last command would yield the correlations between column 1 and 2 of the first 50 and of the last 50 values. Any ideas? Jannis On 27.06.2013 21:43, Greg Snow wrote: Look at the plyr package, probably the ddply function in that package. You can write your own function to do whatever you want on the pieces of the split apart object. Correlation between a specified pair of columns would be simple. On Thu, Jun 27, 2013 at 11:26 AM, Jannis bt_jan...@yahoo.de wrote: Dear List members, i am seeking a multivariate version of aggregate. I want to compute, fro example the correlation between subsets of two vectors. In aggregate, i can only supply one vector with indices for subsets. Is there ready function for this or do i need to program my own? Cheers Jannis __** R-help@r-project.org mailing list https://stat.ethz.ch/mailman/**listinfo/r-helphttps://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/** posting-guide.html http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Scatter plot with error bars
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. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] multivariate version of aggregate
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: Jannis bt_jan...@yahoo.de To: Greg Snow 538...@gmail.com Cc: r-help r-help@r-project.org Sent: Friday, June 28, 2013 4:31 AM Subject: Re: [R] multivariate version of aggregate 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(.data = testframe, INDICES= indices, .fun = function(x) corr(x[,1], x[,2])) Where the last command would yield the correlations between column 1 and 2 of the first 50 and of the last 50 values. Any ideas? Jannis On 27.06.2013 21:43, Greg Snow wrote: Look at the plyr package, probably the ddply function in that package. You can write your own function to do whatever you want on the pieces of the split apart object. Correlation between a specified pair of columns would be simple. On Thu, Jun 27, 2013 at 11:26 AM, Jannis bt_jan...@yahoo.de wrote: Dear List members, i am seeking a multivariate version of aggregate. I want to compute, fro example the correlation between subsets of two vectors. In aggregate, i can only supply one vector with indices for subsets. Is there ready function for this or do i need to program my own? Cheers Jannis __** R-help@r-project.org mailing list https://stat.ethz.ch/mailman/**listinfo/r-helphttps://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/** posting-guide.html http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] multiple csv files for T-test
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,20:40),40,replace=TRUE),ncol=4))
set.seed(285)
dat2- as.data.frame(matrix(sample(c(NA,35:60),40,replace=TRUE),ncol=4))
sapply(colnames(dat1),function(i)
t.test(dat1[,i],dat2[,i],paired=TRUE)$p.value)
# V1 V2 V3 V4
#7.004488e-05 1.374986e-03 6.666004e-04 3.749257e-04
#Removing missing values and then do the test
sapply(colnames(dat1),function(i)
{x1-na.omit(cbind(dat1[,i],dat2[,i]));t.test(x1[,1],x1[,2],paired=TRUE)$p.value})
# V1 V2 V3 V4
#7.004488e-05 1.374986e-03 6.666004e-04 3.749257e-04
A.K.
thanks very much, you're help is much appreciated.
Just another small question, what's the best way to deal with missing data? If
i want to do a paired t-test?
- Original Message -
From: arun smartpink...@yahoo.com
To: R help r-help@r-project.org
Cc:
Sent: Thursday, June 27, 2013 1:47 PM
Subject: Re: multiple csv files for T-test
Hi,
I used as.data.frame(matrix(...)) just to create an example dataset. In your
case, you don't need to do that. Using the same example:
set.seed(24)
dat1- as.data.frame(matrix(sample(20:40,40,replace=TRUE),ncol=4))
set.seed(285)
dat2- as.data.frame(matrix(sample(35:60,40,replace=TRUE),ncol=4))
write.csv(dat1,file1.csv,row.names=FALSE)
write.csv(dat2,file2.csv,row.names=FALSE)
data1- read.csv(file1.csv)
data2- read.csv(file2.csv)
###Your code:
dat1New- as.data.frame(matrix(data1))
dat2New- as.data.frame(matrix(data2))
###It is always useful to check ?str()
str(dat1New)
#'data.frame': 4 obs. of 1 variable:
# $ V1:List of 4
# ..$ : int 26 24 34 30 33 39 25 36 36 25
#..$ : int 32 27 34 34 26 38 24 20 30 22
# ..$ : int 21 31 35 22 24 34 21 32 33 20
#..$ : int 26 25 27 23 39 24 35 33 34 40
dat1New
# V1
#1 26, 24, 34, 30, 33, 39, 25, 36, 36, 25
#2 32, 27, 34, 34, 26, 38, 24, 20, 30, 22
#3 21, 31, 35, 22, 24, 34, 21, 32, 33, 20
#4 26, 25, 27, 23, 39, 24, 35, 33, 34, 40
dat2New
# V1
#1 53, 40, 47, 57, 57, 53, 35, 42, 53, 41
#2 54, 37, 43, 40, 57, 42, 37, 53, 60, 39
#3 54, 60, 46, 50, 35, 41, 58, 45, 36, 53
#4 52, 56, 44, 40, 38, 53, 47, 46, 60, 50
sapply(colnames(dat1New),function(i)
t.test(dat1New[,i],dat2New[,i],paired=TRUE)$p.value)
#Error in x - y : non-numeric argument to binary operator
##Just using data1 and data2
sapply(colnames(data1),function(i)
t.test(data1[,i],data2[,i],paired=TRUE)$p.value)
# V1 V2 V3 V4
#3.202629e-05 6.510644e-04 6.215225e-04 3.044760e-04
#or using dat1New and dat2New
sapply(seq_along(dat1New$V1),function(i)
t.test(dat1New$V1[[i]],dat2New$V1[[i]],paired=TRUE)$p.value)
#[1] 3.202629e-05 6.510644e-04 6.215225e-04 3.044760e-04
A.K.
thanks for the reply, I am getting the following error
Error in x - y : non-numeric argument to binary operator
This is what I enter below
data1 -read.csv(file1.csv)
data2 -read.csv(file2.csv)
dat1- as.data.frame(matrix(data1))
dat2- as.data.frame(matrix(data2))
sapply(colnames(dat1),function(i)
t.test(dat1[,i],dat2[,i],paired=TRUE)$p.value)
As far as I can see all my values are numeric...?
- Original Message -
From: arun smartpink...@yahoo.com
To: R help r-help@r-project.org
Cc:
Sent: Thursday, June 27, 2013 10:17 AM
Subject: Re: multiple csv files for T-test
Hi,
May be this helps:
#You can use ?read.csv() to read the two files.
set.seed(24)
dat1- as.data.frame(matrix(sample(20:40,40,replace=TRUE),ncol=4))
set.seed(285)
dat2- as.data.frame(matrix(sample(35:60,40,replace=TRUE),ncol=4))
sapply(colnames(dat1),function(i) t.test(dat1[,i],dat2[,i],paired=TRUE)$p.value)
# V1 V2 V3 V4
#3.202629e-05 6.510644e-04 6.215225e-04 3.044760e-04
A.K.
Hi
I am fairly new to R so if this is a stupid question please forgive me.
I have a CSV file with multiple parameters (50). I have another
CSV file with the same parameters after treatment. Is there a way I
can read these two files into R and do multiple paired T-test as all the
parameters are in the same columns in each file?
Thanks in advance
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Re: [R] Changing legend to fill colour in ggplot
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 a representative sample. We currrently have no idea of what the graph looks like as the R-help list strips that out .With the actual data a reader can just copy it and your code into R and see exactly what you are getting. Please don't post in HTML. Plain text is much easier to read, the HTML gets dropped and any formating goes to pot. I think the actual answer is probably straight forward but we really should have the data Thanks John Kane Kingston ON Canada -Original Message- From: suparna.mitra...@gmail.com Sent: Fri, 28 Jun 2013 13:25:59 +0800 To: r-help@r-project.org Subject: [R] Changing legend to fill colour in ggplot 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 2 2 $ species : Factor w/ 5 levels acinetobacter_sp,..: 2 5 1 4 3 2 5 1 4 3 $ genome_coverage_bp: int 8196 3405 8625 22568 2128 6100 1841 3914 8487 1064 $ genome_length : int 3571237 2541445 3912725 3479613 5460977 3571237 2541445 3912725 3479613 5460977 $ genome_coverage_percentage: Factor w/ 10 levels 0.02%,0.04%,..: 8 5 7 10 2 6 3 4 9 1 $ avg_depth_coverage: num 121.96 2.81 19.84 399.63 1.64 ... Now what I did is p=ggplot(df,aes(genome_coverage_percentage,avg_depth_coverage))+geom_point(aes(colour = species,shape = factor(id))) p+scale_shape_discrete(name =,labels=c(Patient 1, Patient 2)) That creats the plot below. But I want to change the circles of legend in fill colour. So that it doesn't look like it is only from Patient 1, as that also has circle. Can anybody help me please? Thanks a lot in advance :) Mitra [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. FREE 3D MARINE AQUARIUM SCREENSAVER - Watch dolphins, sharks orcas on your desktop! __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] choicemodelr is misbehaving under R3.0
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 - and only R gui is used, the package works just fine. However, when RStudio is used with R3.0 then the computations by ChoiceModelR take hours instead of minutes. The problem has been replicated with different Windows 7 PCs (32 and 64 bits) and even with a Linux computer. We are not sure if the same kind of problem exists for other R packages - when one uses RStudio in combination with R3.0. Could you please look into it? Thank you very much! Dimitri On Thu, Jun 27, 2013 at 10:37 AM, Dimitri Liakhovitski dimitri.liakhovit...@gmail.com wrote: Hi John (and other authors of ChoiceModelR package), I am experiencing a weird thing when using the function choicemodelr under R3.0.1. Before I updated to R3.0, I had used choicemodelr unde R2.15. It was always as fast or faster than exactly the same task in Sawtooth software. Now, I've tried to run it under R3.0.1. It seems to be doing the job. But something is slowing it down dramatically. In the beginning, it showed time left for estimation as 14 min. But then time passed and the time left increased(!) instead of decreasing. My whole run took 1.8 hours. I've run the same thing in Sawtooth - it took 13 min. I replicated the same result under different conditions (restarted my PC, had no other stuff running). My PC is a 64-bit PC (Windows). Then I asked a colleague who also has R3.0 on his PC to run my code. His PC is a 32-bit one (Windows). Same thing happened to him. It showed time left as 14 min in the beginning and then the time left started growing. Then, I asked a colleague who has R2.15 (on a 32-bit Windows machine) to run my code. It took him 12 minutes! So, something is going on with ChoiceModelR unde R3.0 Thanks for looking into it. -- Dimitri Liakhovitski -- Dimitri Liakhovitski [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] How to create a function returning an array ?
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) for instance
-
read_ts-function(n,m,o,img) {
out-.Fortran(read_ts,
as.integer(n),
as.integer(m),
as.integer(o),
img=as.single(rnorm(n)))
return(out$img)
--
Well, assuming that the 'out$img' object has a R-length of n*m*o , wouldn't if
be simpler to just change the return call to:
In fact, out$img has a length of n, same as on input. .Fortran won't
change the length of its arguments.
Duncan Murdoch
return( array( out$img, dim=c(n,m,o) )
I don't think you wnat start naming your dimension vectors c.
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and provide commented, minimal, self-contained, reproducible code.
Re: [R] choicemodelr is misbehaving under R3.0
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 Kane Kingston ON Canada -Original Message- From: dimitri.liakhovit...@gmail.com Sent: Fri, 28 Jun 2013 09:11:40 -0400 To: r-help@r-project.org, jcol...@decisionanalyst.com, i...@rstudio.com Subject: Re: [R] choicemodelr is misbehaving under R3.0 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 - and only R gui is used, the package works just fine. However, when RStudio is used with R3.0 then the computations by ChoiceModelR take hours instead of minutes. The problem has been replicated with different Windows 7 PCs (32 and 64 bits) and even with a Linux computer. We are not sure if the same kind of problem exists for other R packages - when one uses RStudio in combination with R3.0. Could you please look into it? Thank you very much! Dimitri On Thu, Jun 27, 2013 at 10:37 AM, Dimitri Liakhovitski dimitri.liakhovit...@gmail.com wrote: Hi John (and other authors of ChoiceModelR package), I am experiencing a weird thing when using the function choicemodelr under R3.0.1. Before I updated to R3.0, I had used choicemodelr unde R2.15. It was always as fast or faster than exactly the same task in Sawtooth software. Now, I've tried to run it under R3.0.1. It seems to be doing the job. But something is slowing it down dramatically. In the beginning, it showed time left for estimation as 14 min. But then time passed and the time left increased(!) instead of decreasing. My whole run took 1.8 hours. I've run the same thing in Sawtooth - it took 13 min. I replicated the same result under different conditions (restarted my PC, had no other stuff running). My PC is a 64-bit PC (Windows). Then I asked a colleague who also has R3.0 on his PC to run my code. His PC is a 32-bit one (Windows). Same thing happened to him. It showed time left as 14 min in the beginning and then the time left started growing. Then, I asked a colleague who has R2.15 (on a 32-bit Windows machine) to run my code. It took him 12 minutes! So, something is going on with ChoiceModelR unde R3.0 Thanks for looking into it. -- Dimitri Liakhovitski -- Dimitri Liakhovitski [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. FREE ONLINE PHOTOSHARING - Share your photos online with your friends and family! Visit http://www.inbox.com/photosharing to find out more! __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Lexical scoping is not what I expect
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 messy, because a) that's true and b) it actually leads to some
genuine risks when 'globals' get redefined or masked*.
How about I amend the assertion to if your code relies on lexical scoping to
find a variable you defined, you should probably rewrite your code.
and leave it at that, subject to some common sense about whether you know what
you're doing?
Steve E
*Example
sin.deg - function(deg) sin(deg * pi/180)
sin.deg(45)
[1] 0.7071068
#looks about right
pi - 3.2 #Indiana General Assembly bill #247, 1897.
sin.deg(45)
[1] 0.7173561
#oops ...
***
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] Lexical scoping is not what I expect
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
scoping to some extent!
This could get messy, because a) that's true and b) it actually leads to some
genuine risks when 'globals' get redefined or masked*.
How about I amend the assertion to if your code relies on lexical scoping to find a
variable you defined, you should probably rewrite your code.
and leave it at that, subject to some common sense about whether you know what
you're doing?
That still isn't right, because users should feel free to define
functions and call them from their other functions.
I think who defined it isn't the issue, the issue is whether it might
change unexpectedly. The user owns globalenv(). The package author
owns the package namespace. So packages should almost never read or
write things directly from/to globalenv() (the user might change them),
but they can create their own private environments and write there.
Where it gets a little less clear is when the user writes a function. I
would say functions should never write directly to globalenv(), but it's
perfectly fine to reference constants there (like other functions
written by the user). Referencing things there that change is the risky
thing.
Duncan Murdoch
Steve E
*Example
sin.deg - function(deg) sin(deg * pi/180)
sin.deg(45)
[1] 0.7071068
#looks about right
pi - 3.2 #Indiana General Assembly bill #247, 1897.
sin.deg(45)
[1] 0.7173561
#oops ...
***
This email and any attachments are confidential. Any use...{{dropped:8}}
__
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] Help with tables
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 03/01/2013 11:23 03/01/2013 213839 fdp.percentage_calc_foundation 57 TRUE 03/01/2013 11:24 03/01/2013 213845 fdp.percentage_calc_foundation 92 TRUE 03/01/2013 11:24 03/01/2013 213852 fdp.percentage_calc_foundation 65 TRUE 03/01/2013 11:24 03/01/2013 213855 fdp.percentage_calc_foundation 111 TRUE 03/01/2013 11:24 03/01/2013 213860 fdp.percentage_calc_foundation 34 TRUE 03/01/2013 11:24 03/01/2013 213864 fdp.percentage_calc_foundation 109 FALSE 03/01/2013 11:24 03/01/2013 213868 fdp.percentage_calc_foundation 148 FALSE 03/01/2013 11:24 03/01/2013 213877 fdp.percentage_calc_foundation 69 FALSE 03/01/2013 11:24 03/01/2013 213878 fdp.percentage_calc_foundation 61 TRUE 03/01/2013 11:24 03/01/2013 213878 fdp.percentage_calc_foundation 11 TRUE 03/01/2013 11:24 03/01/2013 213879 algebra.core.formulae 134 TRUE 03/01/2013 11:24 03/01/2013 213881 fdp.percentage_calc_foundation 63 TRUE 03/01/2013 11:24 03/01/2013 213886 fdp.percentage_calc_foundation 40 TRUE 03/01/2013 11:24 03/01/2013 213887 algebra.core.formulae 68 TRUE 03/01/2013 11:24 03/01/2013 213898 fdp.percentage_calc_foundation 109 TRUE 03/01/2013 11:24 03/01/2013 213899 algebra.core.formulae 111 TRUE 03/01/2013 11:25 03/01/2013 213901 algebra.core.formulae 101 FALSE 03/01/2013 11:25 03/01/2013 213924 fdp.percentage_calc_foundation 150 TRUE 03/01/2013 11:25 03/01/2013 213958 fdp.percentage_calc_foundation 77 TRUE 03/01/2013 11:25 03/01/2013 213959 fdp.percentage_calc_foundation 134 TRUE 03/01/2013 11:26 03/01/2013 213961 algebra.core.formulae 150 TRUE 03/01/2013 11:26 03/01/2013 214007 algebra.core.formulae 114 TRUE 03/01/2013 11:26 03/01/2013 214008 fdp.percentage_calc_foundation 55 FALSE 03/01/2013 11:26 03/01/2013 214009 fdp.percentage_calc_foundation 67 TRUE 03/01/2013 11:26 03/01/2013 214010 fdp.percentage_calc_foundation 24 TRUE 03/01/2013 11:26 03/01/2013 214014 algebra.core.formulae 114 TRUE 03/01/2013 11:26 03/01/2013 214014 algebra.core.equations 55 TRUE 03/01/2013 11:26 03/01/2013 214015 algebra.core.formulae 97 TRUE 03/01/2013 11:26 03/01/2013 214015 fdp.percentage_calc_foundation 154 FALSE 03/01/2013 11:26 03/01/2013 214017 algebra.core.formulae 21 FALSE 03/01/2013 11:26 03/01/2013 214017 fdp.percentage_calc_foundation 24 TRUE 03/01/2013 11:26 03/01/2013 214019 fdp.percentage_calc_foundation 149 TRUE 03/01/2013 11:26 03/01/2013 214019 fdp.percentage_calc_foundation 119 TRUE 03/01/2013 11:27 03/01/2013 214022 algebra.core.formulae 21 TRUE 03/01/2013 11:27 03/01/2013 214023 algebra.core.formulae 103 TRUE 03/01/2013 11:27 03/01/2013 214023 fdp.percentage_calc_foundation 55 TRUE 03/01/2013 11:27 03/01/2013 214024 fdp.percentage_calc_foundation 24 TRUE 03/01/2013 11:27 03/01/2013 214026 algebra.core.formulae 149 TRUE 03/01/2013 11:27 03/01/2013 214026 fdp.percentage_calc_foundation 154 TRUE 03/01/2013 11:27 03/01/2013 214027 algebra.core.formulae 24 TRUE 03/01/2013 11:27 03/01/2013 214078 algebra.core.equations 67 FALSE 03/01/2013 11:28 03/01/2013 214085 fdp.percentage_calc_foundation 119 TRUE 03/01/2013 11:28 03/01/2013 214085 fdp.percentage_calc_foundation 55 FALSE 03/01/2013 11:28 03/01/2013 214085 fdp.percentage_calc_foundation 149 TRUE 03/01/2013 11:28 03/01/2013 214086 algebra.core.formulae 67 FALSE 03/01/2013 11:29 03/01/2013 214169 algebra.core.formulae 92 TRUE 03/01/2013 11:29 03/01/2013 214172 algebra.core.formulae 15 TRUE 03/01/2013 11:29 03/01/2013 214172 algebra.core.equations 119 TRUE 03/01/2013 11:29 03/01/2013 214173 algebra.core.formulae 46 TRUE 03/01/2013 11:29 03/01/2013 214173 fdp.percentage_calc_foundation 146 TRUE ,sep=,header=TRUE,stringsAsFactors=FALSE) dat2- data.frame(timestamp=as.POSIXct(paste(dat1[,1],dat1[,2]),format=%m/%d/%Y %H:%M), dat1[,-c(1:2)]) library(xts) xt1- xts(dat2[,-1],dat2[,1]) library(stringr) ##1st part nrow(xt1[2013-03-01 11:15/2013-03-01 11:28]) #[1] 46 ##2nd part table(xt1[2013-03-01 11:15/2013-03-01 11:28,topic]) # # algebra.core.equations algebra.core.formulae # 2 14 #fdp.percentage_calc_foundation # 30 ###3rd question Subxt1-xt1[2013-03-01 11:15/2013-03-01 11:28] #Based on number of correct responses vec1-sort(with(Subxt1,tapply(as.logical(str_trim(correct)),list(pupilId),sum))) head(vec1,3) #101 148 69 # 0 0 0 tail(vec1,3) # 55 149 24 # 2 3 4 #Based on proportion of correct responses vec2-with(Subxt1,tapply(as.logical(str_trim(correct)),list(pupilId),length)) vec2New- vec2[names(vec1)] vec3-sort(vec1/vec2New) head(vec3,3) #101 148 69 # 0 0 0 tail(vec3,3) #150 149 24 # 1 1 1 A.K. For date 03/01/2013 I need to find how many responses I have between 11.15 and
Re: [R] Data Package Query
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 explore your R in-memory environment, and use the built-in help system with the question mark (?str) or the help.search() and RSiteSearch() functions. --- Jeff NewmillerThe . . Go Live... DCN:jdnew...@dcn.davis.ca.usBasics: ##.#. ##.#. Live Go... Live: OO#.. Dead: OO#.. Playing Research Engineer (Solar/BatteriesO.O#. #.O#. with /Software/Embedded Controllers) .OO#. .OO#. rocks...1k --- Sent from my phone. Please excuse my brevity. Yasmine Refai y_re...@hotmail.com wrote: 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, yasmine Date: Fri, 28 Jun 2013 10:29:21 +1200 From: rolf.tur...@xtra.co.nz To: jdnew...@dcn.davis.ca.us CC: y_re...@hotmail.com; r-help@r-project.org Subject: Re: [R] Data Package Query On 28/06/13 04:47, Jeff Newmiller wrote: SNIP A common error by beginners (which may or may not be your problem in this case) is to create a variable called data. Unfortunately this hides the function named data and from that time forward that R session doesn't work when you type example code that uses the data function. SNIP This is simply not true. I believe it *used* to be true, sometime wa back, but hasn't been true for years. The R language is much cleverer now. If there is a function melvin() somewhere on the search path and also a data object melvin (earlier on the search path) then doing melvin(whatever) will correctly call the function melvin() with no complaints. The R language can tell by the parentheses that you mean the *function* melvin and not the data object melvin. E.g. data - 42 require(akima) akima Error: object 'akima' not found data(akima) # No error message, nor nothin'! akima # The data set akima is displayed. All that being said it is ***BAD PRACTICE***, just in terms of comprehensibility and avoiding confusion, to give a data set set the same name as a function (either built in, or one of your own). fortune(dog) is relevant. cheers, Rolf Turner __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] How to create a function returning an array ?
@ 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$img)
alpha-read_ts(n,m)
dim(alpha)-c(n*m)
alpha-t(alpha)
My worry with this syntax is that (i) the program is not very efficient because
n and m are very big and these two additional instructions (dim(alpha)-c(n*m
and alpha-t(alpha) can be skipped just by directly declaring img as an array
in fortran instead of a vector and (ii) the syntax will become more complex
dealing with a multidimensional array instead of a matrix as in this example.
And this is why I'm looking for the correct instruction to declare img as an
array instead of a vector.
Armel
-Original Message-
From: Duncan Murdoch [mailto:murdoch.dun...@gmail.com]
Sent: Friday, June 28, 2013 8:16 AM
To: David Winsemius
Cc: Kaptue Tchuente, Armel; r-help@r-project.org
Subject: Re: [R] How to create a function returning an array ?
On 27/06/2013 11:38 PM, David Winsemius wrote:
On Jun 27, 2013, at 8:04 PM, Kaptue Tchuente, Armel wrote:
Hi there,
I would like to know how to change the line
img=as.single(rnorm(m))) such that instead of being a vector of
length m as it is now, img is an array of dimension c=(n,m,o) for
instance
-
read_ts-function(n,m,o,img) {
out-.Fortran(read_ts,
as.integer(n),
as.integer(m),
as.integer(o),
img=as.single(rnorm(n)))
return(out$img)
--
Well, assuming that the 'out$img' object has a R-length of n*m*o , wouldn't
if be simpler to just change the return call to:
In fact, out$img has a length of n, same as on input. .Fortran won't change
the length of its arguments.
Duncan Murdoch
return( array( out$img, dim=c(n,m,o) )
I don't think you wnat start naming your dimension vectors c.
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] How to create a function returning an array ?
On 28/06/2013 10:18 AM, Kaptue Tchuente, Armel wrote:
@ Duncan, I have already used the syntax that you proposed before asking for
help by writing something like
read_ts-function(n,m,img) {
out-.Fortran(read_ts,
as.integer(n),
as.integer(m),
img=as.single(rnorm(n*m)))
return(out$img)
alpha-read_ts(n,m)
dim(alpha)-c(n*m)
alpha-t(alpha)
My worry with this syntax is that (i) the program is not very efficient because n and
m are very big and these two additional instructions (dim(alpha)-c(n*m and
alpha-t(alpha) can be skipped just by directly declaring img as an array in
fortran instead of a vector and (ii) the syntax will become more complex dealing with
a multidimensional array instead of a matrix as in this example.
And this is why I'm looking for the correct instruction to declare img as an
array instead of a vector.
There are several typos in your code above, but I think your intention
is clear.
You can do what you are asking for, but not with .Fortran. It only
handles vectors for input and output. You'll need to use .Call (which
means writing in C or C++). If you're familiar with C++, using Rcpp is
probably the easiest way to do this. If not, I'd rewrite the Fortran
code to avoid the need for the transpose at the end, and do
dim(out$img) - c(n,m)
return(out$img)
within your read_ts function. I think this is reasonably efficient.
Duncan Murdoch
Armel
-Original Message-
From: Duncan Murdoch [mailto:murdoch.dun...@gmail.com]
Sent: Friday, June 28, 2013 8:16 AM
To: David Winsemius
Cc: Kaptue Tchuente, Armel; r-help@r-project.org
Subject: Re: [R] How to create a function returning an array ?
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) for
instance
-
read_ts-function(n,m,o,img) {
out-.Fortran(read_ts,
as.integer(n),
as.integer(m),
as.integer(o),
img=as.single(rnorm(n)))
return(out$img)
--
Well, assuming that the 'out$img' object has a R-length of n*m*o , wouldn't
if be simpler to just change the return call to:
In fact, out$img has a length of n, same as on input. .Fortran won't change
the length of its arguments.
Duncan Murdoch
return( array( out$img, dim=c(n,m,o) )
I don't think you wnat start naming your dimension vectors c.
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] How to create a function returning an array ?
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 call this fortran function because I
realized that (i) R is not very efficient for large data sets reading and
processing and (ii) the speed of execution in Fortran is faster than in C.
Armel
-Original Message-
From: Duncan Murdoch [mailto:murdoch.dun...@gmail.com]
Sent: Friday, June 28, 2013 9:30 AM
To: Kaptue Tchuente, Armel
Cc: r-help@r-project.org
Subject: Re: [R] How to create a function returning an array ?
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),
img=as.single(rnorm(n*m)))
return(out$img)
alpha-read_ts(n,m)
dim(alpha)-c(n*m)
alpha-t(alpha)
My worry with this syntax is that (i) the program is not very efficient
because n and m are very big and these two additional instructions
(dim(alpha)-c(n*m and alpha-t(alpha) can be skipped just by directly
declaring img as an array in fortran instead of a vector and (ii) the syntax
will become more complex dealing with a multidimensional array instead of a
matrix as in this example.
And this is why I'm looking for the correct instruction to declare img as an
array instead of a vector.
There are several typos in your code above, but I think your intention is clear.
You can do what you are asking for, but not with .Fortran. It only handles
vectors for input and output. You'll need to use .Call (which means writing in
C or C++). If you're familiar with C++, using Rcpp is probably the easiest way
to do this. If not, I'd rewrite the Fortran code to avoid the need for the
transpose at the end, and do
dim(out$img) - c(n,m)
return(out$img)
within your read_ts function. I think this is reasonably efficient.
Duncan Murdoch
Armel
-Original Message-
From: Duncan Murdoch [mailto:murdoch.dun...@gmail.com]
Sent: Friday, June 28, 2013 8:16 AM
To: David Winsemius
Cc: Kaptue Tchuente, Armel; r-help@r-project.org
Subject: Re: [R] How to create a function returning an array ?
On 27/06/2013 11:38 PM, David Winsemius wrote:
On Jun 27, 2013, at 8:04 PM, Kaptue Tchuente, Armel wrote:
Hi there,
I would like to know how to change the line
img=as.single(rnorm(m))) such that instead of being a vector of
length m as it is now, img is an array of dimension c=(n,m,o) for
instance
-
read_ts-function(n,m,o,img) {
out-.Fortran(read_ts,
as.integer(n),
as.integer(m),
as.integer(o),
img=as.single(rnorm(n)))
return(out$img)
--
Well, assuming that the 'out$img' object has a R-length of n*m*o ,
wouldn't if be simpler to just change the return call to:
In fact, out$img has a length of n, same as on input. .Fortran won't change
the length of its arguments.
Duncan Murdoch
return( array( out$img, dim=c(n,m,o) )
I don't think you wnat start naming your dimension vectors c.
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] How to create a function returning an array ?
On 28/06/2013 10:46 AM, Kaptue Tchuente, Armel wrote:
Please could you explain what you mean by several typos in my code?
1. img is passed as an argument, but never used.
2. There is no closing brace on the function body.
3. You set the dimension to n*m, when I believe you wanted c(n, m).
Duncan Murdoch
Anyway, it works very well and keep in minds that here I just wrote a very
simple code to illustrate what I really want since in the reality, the program
is more complex than what you see.
May be I'm wrong but I also prefer to call this fortran function because I
realized that (i) R is not very efficient for large data sets reading and
processing and (ii) the speed of execution in Fortran is faster than in C.
Armel
-Original Message-
From: Duncan Murdoch [mailto:murdoch.dun...@gmail.com]
Sent: Friday, June 28, 2013 9:30 AM
To: Kaptue Tchuente, Armel
Cc: r-help@r-project.org
Subject: Re: [R] How to create a function returning an array ?
On 28/06/2013 10:18 AM, Kaptue Tchuente, Armel wrote:
@ Duncan, I have already used the syntax that you proposed before
asking for help by writing something like
read_ts-function(n,m,img) {
out-.Fortran(read_ts,
as.integer(n),
as.integer(m),
img=as.single(rnorm(n*m)))
return(out$img)
alpha-read_ts(n,m)
dim(alpha)-c(n*m)
alpha-t(alpha)
My worry with this syntax is that (i) the program is not very efficient because n
and m are very big and these two additional instructions (dim(alpha)-c(n*m and
alpha-t(alpha) can be skipped just by directly declaring img as an array in fortran
instead of a vector and (ii) the syntax will become more complex dealing with a
multidimensional array instead of a matrix as in this example.
And this is why I'm looking for the correct instruction to declare img as an
array instead of a vector.
There are several typos in your code above, but I think your intention is clear.
You can do what you are asking for, but not with .Fortran. It only handles
vectors for input and output. You'll need to use .Call (which means writing in
C or C++). If you're familiar with C++, using Rcpp is probably the easiest way
to do this. If not, I'd rewrite the Fortran code to avoid the need for the
transpose at the end, and do
dim(out$img) - c(n,m)
return(out$img)
within your read_ts function. I think this is reasonably efficient.
Duncan Murdoch
Armel
-Original Message-
From: Duncan Murdoch [mailto:murdoch.dun...@gmail.com]
Sent: Friday, June 28, 2013 8:16 AM
To: David Winsemius
Cc: Kaptue Tchuente, Armel; r-help@r-project.org
Subject: Re: [R] How to create a function returning an array ?
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) for
instance
-
read_ts-function(n,m,o,img) {
out-.Fortran(read_ts,
as.integer(n),
as.integer(m),
as.integer(o),
img=as.single(rnorm(n)))
return(out$img)
--
Well, assuming that the 'out$img' object has a R-length of n*m*o ,
wouldn't if be simpler to just change the return call to:
In fact, out$img has a length of n, same as on input. .Fortran won't change
the length of its arguments.
Duncan Murdoch
return( array( out$img, dim=c(n,m,o) )
I don't think you wnat start naming your dimension vectors c.
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Re: [R] Lexical scoping is not what I expect
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
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
project.org] On Behalf Of Duncan Murdoch
Sent: Friday, June 28, 2013 9:40 AM
To: S Ellison
Cc: r-help@r-project.org
Subject: Re: [R] Lexical scoping is not what I expect
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
scoping to some extent!
This could get messy, because a) that's true and b) it actually leads
to some genuine risks when 'globals' get redefined or masked*.
How about I amend the assertion to if your code relies on lexical
scoping to find a variable you defined, you should probably rewrite
your code.
and leave it at that, subject to some common sense about whether you
know what you're doing?
That still isn't right, because users should feel free to define
functions and call them from their other functions.
I think who defined it isn't the issue, the issue is whether it might
change unexpectedly. The user owns globalenv(). The package author
owns the package namespace. So packages should almost never read or
write things directly from/to globalenv() (the user might change them),
but they can create their own private environments and write there.
Where it gets a little less clear is when the user writes a function.
I
would say functions should never write directly to globalenv(), but
it's
perfectly fine to reference constants there (like other functions
written by the user). Referencing things there that change is the
risky
thing.
Duncan Murdoch
Steve E
*Example
sin.deg - function(deg) sin(deg * pi/180)
sin.deg(45)
[1] 0.7071068
#looks about right
pi - 3.2 #Indiana General Assembly bill #247, 1897.
sin.deg(45)
[1] 0.7173561
#oops ...
***
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use...{{dropped:8}}
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Re: [R] Lexical scoping is not what I expect
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 TRUE, Inf, etc.?
If we weren't allowed to change T and F, would we be allowed to change
other constants, like functions mean or max? If we couldn't change
anything defined in the base package, would we be allowed to change
things defined in other packages like stats or utils or graphics? I
think it's simply a matter of setting the line somewhere, and R has
chosen to set it in the most permissive place that's reasonable. It
assumes that its users know what they are doing.
Why not allow changes to TRUE or Inf? TRUE is a constant, whereas T is
a variable containing TRUE. Inf is also a constant, corresponding to a
length one vector containing that value. Those are treated by the
parser like 2 or hello. It would be really bad if someone could
change the meaning of 2 (though I hear some old Fortran compilers
allowed that), but is it really so bad to allow someone to define their
own plot function, or temperature variable named T?
Duncan Murdoch
Best,
John
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
project.org] On Behalf Of Duncan Murdoch
Sent: Friday, June 28, 2013 9:40 AM
To: S Ellison
Cc: r-help@r-project.org
Subject: Re: [R] Lexical scoping is not what I expect
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
scoping to some extent!
This could get messy, because a) that's true and b) it actually leads
to some genuine risks when 'globals' get redefined or masked*.
How about I amend the assertion to if your code relies on lexical
scoping to find a variable you defined, you should probably rewrite
your code.
and leave it at that, subject to some common sense about whether you
know what you're doing?
That still isn't right, because users should feel free to define
functions and call them from their other functions.
I think who defined it isn't the issue, the issue is whether it might
change unexpectedly. The user owns globalenv(). The package author
owns the package namespace. So packages should almost never read or
write things directly from/to globalenv() (the user might change them),
but they can create their own private environments and write there.
Where it gets a little less clear is when the user writes a function.
I
would say functions should never write directly to globalenv(), but
it's
perfectly fine to reference constants there (like other functions
written by the user). Referencing things there that change is the
risky
thing.
Duncan Murdoch
Steve E
*Example
sin.deg - function(deg) sin(deg * pi/180)
sin.deg(45)
[1] 0.7071068
#looks about right
pi - 3.2 #Indiana General Assembly bill #247, 1897.
sin.deg(45)
[1] 0.7173561
#oops ...
***
This email and any attachments are confidential. Any
use...{{dropped:8}}
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-
guide.html
and provide commented, minimal, self-contained, reproducible code.
__
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PLEASE do read the posting guide http://www.R-project.org/posting-
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and provide commented, minimal, self-contained, reproducible code.
__
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] Lexical scoping is not what I expect
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, Inf, etc.?
Because people wanted to use them as names of things. Maybe a T (not t)
statistic.
And BTW, you can change the value of T for yourself, but you will not
change it for any package code, including R itself, since the base
namespace is ahead of the workspace in namespace scoping. Because of
that, it is years since I have seen anyone actually trip themselves up
over this.
Best,
John
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
project.org] On Behalf Of Duncan Murdoch
Sent: Friday, June 28, 2013 9:40 AM
To: S Ellison
Cc: r-help@r-project.org
Subject: Re: [R] Lexical scoping is not what I expect
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
scoping to some extent!
This could get messy, because a) that's true and b) it actually leads
to some genuine risks when 'globals' get redefined or masked*.
How about I amend the assertion to if your code relies on lexical
scoping to find a variable you defined, you should probably rewrite
your code.
and leave it at that, subject to some common sense about whether you
know what you're doing?
That still isn't right, because users should feel free to define
functions and call them from their other functions.
I think who defined it isn't the issue, the issue is whether it might
change unexpectedly. The user owns globalenv(). The package author
owns the package namespace. So packages should almost never read or
write things directly from/to globalenv() (the user might change them),
but they can create their own private environments and write there.
Where it gets a little less clear is when the user writes a function.
I
would say functions should never write directly to globalenv(), but
it's
perfectly fine to reference constants there (like other functions
written by the user). Referencing things there that change is the
risky
thing.
Duncan Murdoch
Steve E
*Example
sin.deg - function(deg) sin(deg * pi/180)
sin.deg(45)
[1] 0.7071068
#looks about right
pi - 3.2 #Indiana General Assembly bill #247, 1897.
sin.deg(45)
[1] 0.7173561
#oops ...
***
This email and any attachments are confidential. Any
use...{{dropped:8}}
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-
guide.html
and provide commented, minimal, self-contained, reproducible code.
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-
guide.html
and provide commented, minimal, self-contained, reproducible code.
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
--
Brian D. Ripley, rip...@stats.ox.ac.uk
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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and provide commented, minimal, self-contained, reproducible code.
Re: [R] How to create a function returning an array ?
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 [mailto:murdoch.dun...@gmail.com]
Sent: Friday, June 28, 2013 9:53 AM
To: Kaptue Tchuente, Armel
Cc: r-help@r-project.org
Subject: Re: [R] How to create a function returning an array ?
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).
Duncan Murdoch
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 call this fortran function because I
realized that (i) R is not very efficient for large data sets reading and
processing and (ii) the speed of execution in Fortran is faster than in C.
Armel
-Original Message-
From: Duncan Murdoch [mailto:murdoch.dun...@gmail.com]
Sent: Friday, June 28, 2013 9:30 AM
To: Kaptue Tchuente, Armel
Cc: r-help@r-project.org
Subject: Re: [R] How to create a function returning an array ?
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),
img=as.single(rnorm(n*m)))
return(out$img)
alpha-read_ts(n,m)
dim(alpha)-c(n*m)
alpha-t(alpha)
My worry with this syntax is that (i) the program is not very efficient
because n and m are very big and these two additional instructions
(dim(alpha)-c(n*m and alpha-t(alpha) can be skipped just by directly
declaring img as an array in fortran instead of a vector and (ii) the
syntax will become more complex dealing with a multidimensional array
instead of a matrix as in this example.
And this is why I'm looking for the correct instruction to declare img as
an array instead of a vector.
There are several typos in your code above, but I think your intention is
clear.
You can do what you are asking for, but not with .Fortran. It only
handles vectors for input and output. You'll need to use .Call (which
means writing in C or C++). If you're familiar with C++, using Rcpp
is probably the easiest way to do this. If not, I'd rewrite the
Fortran code to avoid the need for the transpose at the end, and do
dim(out$img) - c(n,m)
return(out$img)
within your read_ts function. I think this is reasonably efficient.
Duncan Murdoch
Armel
-Original Message-
From: Duncan Murdoch [mailto:murdoch.dun...@gmail.com]
Sent: Friday, June 28, 2013 8:16 AM
To: David Winsemius
Cc: Kaptue Tchuente, Armel; r-help@r-project.org
Subject: Re: [R] How to create a function returning an array ?
On 27/06/2013 11:38 PM, David Winsemius wrote:
On Jun 27, 2013, at 8:04 PM, Kaptue Tchuente, Armel wrote:
Hi there,
I would like to know how to change the line
img=as.single(rnorm(m))) such that instead of being a vector
of length m as it is now, img is an array of dimension c=(n,m,o)
for instance
-
read_ts-function(n,m,o,img) {
out-.Fortran(read_ts,
as.integer(n),
as.integer(m),
as.integer(o),
img=as.single(rnorm(n)))
return(out$img)
--
Well, assuming that the 'out$img' object has a R-length of n*m*o ,
wouldn't if be simpler to just change the return call to:
In fact, out$img has a length of n, same as on input. .Fortran won't
change the length of its arguments.
Duncan Murdoch
return( array( out$img, dim=c(n,m,o) )
I don't think you wnat start naming your dimension vectors c.
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] Lexical scoping is not what I expect
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 variable T for temperature or F for an
F-value (or pi for what?), nothing fundamental is gained by the ability to
do so (one could use temp or fvalue or Pi), while in the case of a function,
one can consciously mask, e.g., the standard mean(). I'm not sure that it's
generally wise for users to redefine functions like mean(), but I can see a
use for the ability to do that.
Please don't feel the need to reply if you don't wish to -- this isn't in my
opinion an important issue.
Best,
John
-Original Message-
From: Duncan Murdoch [mailto:murdoch.dun...@gmail.com]
Sent: Friday, June 28, 2013 11:07 AM
To: John Fox
Cc: 'S Ellison'; r-help@r-project.org
Subject: Re: [R] Lexical scoping is not what I expect
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 TRUE, Inf, etc.?
If we weren't allowed to change T and F, would we be allowed to change
other constants, like functions mean or max? If we couldn't change
anything defined in the base package, would we be allowed to change
things defined in other packages like stats or utils or graphics? I
think it's simply a matter of setting the line somewhere, and R has
chosen to set it in the most permissive place that's reasonable. It
assumes that its users know what they are doing.
Why not allow changes to TRUE or Inf? TRUE is a constant, whereas T
is
a variable containing TRUE. Inf is also a constant, corresponding to a
length one vector containing that value. Those are treated by the
parser like 2 or hello. It would be really bad if someone could
change the meaning of 2 (though I hear some old Fortran compilers
allowed that), but is it really so bad to allow someone to define their
own plot function, or temperature variable named T?
Duncan Murdoch
Best,
John
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
project.org] On Behalf Of Duncan Murdoch
Sent: Friday, June 28, 2013 9:40 AM
To: S Ellison
Cc: r-help@r-project.org
Subject: Re: [R] Lexical scoping is not what I expect
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
scoping to some extent!
This could get messy, because a) that's true and b) it actually
leads
to some genuine risks when 'globals' get redefined or masked*.
How about I amend the assertion to if your code relies on
lexical
scoping to find a variable you defined, you should probably rewrite
your code.
and leave it at that, subject to some common sense about whether
you
know what you're doing?
That still isn't right, because users should feel free to define
functions and call them from their other functions.
I think who defined it isn't the issue, the issue is whether it
might
change unexpectedly. The user owns globalenv(). The package
author
owns the package namespace. So packages should almost never read
or
write things directly from/to globalenv() (the user might change
them),
but they can create their own private environments and write there.
Where it gets a little less clear is when the user writes a
function.
I
would say functions should never write directly to globalenv(), but
it's
perfectly fine to reference constants there (like other functions
written by the user). Referencing things there that change is the
risky
thing.
Duncan Murdoch
Steve E
*Example
sin.deg - function(deg) sin(deg * pi/180)
sin.deg(45)
[1] 0.7071068
#looks about right
pi - 3.2 #Indiana General Assembly bill #247, 1897.
sin.deg(45)
[1] 0.7173561
#oops ...
***
This email and any attachments are confidential. Any
use...{{dropped:8}}
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-
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guide.html
and provide commented, minimal, self-contained, reproducible
code.
[R] use of formula in survey analysis with replicated weights
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. library(survey) library(quantreg) data(api) ## one-stage cluster sample dclus1-svydesign( id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc) ## convert to bootstrap bclus1-as.svrepdesign( dclus1, type=bootstrap, replicates=100) ## median regression withReplicates( bclus1, quote( coef( rq( api00~api99, tau=0.5, weights=.weights theta SE (Intercept) 87.78505 18.850 api990.91589 0.028 # Defining formula outside Myformula - as.formula( api00~api99) # Rerun the same analysis withReplicates( bclus1, quote( coef( rq( formula= Myformula, tau=0.5, weights=.weights Erreur dans eval(expr, envir, enclos) : objet 'api00' introuvable # I suspect the evaluation not done in the right environment. #If you specify with data option in rq, the initial dataframe, formula is then correctly evaluated but .weights are not found. withReplicates( bclus1, quote( coef( rq( formula= Myformula, tau=0.5, weights=.weights, data=apiclus1 Erreur dans eval(expr, envir, enclos) : objet '.weights' introuvable Any help greatly appreciated O__ Alain Le Tertre c/ /'_ --- Institut de Veille Sanitaire (InVS)/ Département Santé Environnement (*) \(*) -- Responsable de l'unité Statistiques Outils ~~ - 12 rue du val d'Osne 94415 Saint Maurice cedex FRANCE Voice: 33 1 41 79 67 62 Fax: 33 1 41 79 67 68 email: a.leter...@invs.sante.fr __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Lexical scoping is not what I expect
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, 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, Inf, etc.?
Because people wanted to use them as names of things. Maybe a T (not
t)
statistic.
And BTW, you can change the value of T for yourself, but you will not
change it for any package code, including R itself, since the base
namespace is ahead of the workspace in namespace scoping. Because of
that, it is years since I have seen anyone actually trip themselves up
over this.
I was unaware that the base namespace is ahead of the workspace in this
context, and that effectively answers my objection.
Thanks,
John
Best,
John
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
project.org] On Behalf Of Duncan Murdoch
Sent: Friday, June 28, 2013 9:40 AM
To: S Ellison
Cc: r-help@r-project.org
Subject: Re: [R] Lexical scoping is not what I expect
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
scoping to some extent!
This could get messy, because a) that's true and b) it actually
leads
to some genuine risks when 'globals' get redefined or masked*.
How about I amend the assertion to if your code relies on lexical
scoping to find a variable you defined, you should probably rewrite
your code.
and leave it at that, subject to some common sense about whether
you
know what you're doing?
That still isn't right, because users should feel free to define
functions and call them from their other functions.
I think who defined it isn't the issue, the issue is whether it
might
change unexpectedly. The user owns globalenv(). The package author
owns the package namespace. So packages should almost never read or
write things directly from/to globalenv() (the user might change
them),
but they can create their own private environments and write there.
Where it gets a little less clear is when the user writes a
function.
I
would say functions should never write directly to globalenv(), but
it's
perfectly fine to reference constants there (like other functions
written by the user). Referencing things there that change is the
risky
thing.
Duncan Murdoch
Steve E
*Example
sin.deg - function(deg) sin(deg * pi/180)
sin.deg(45)
[1] 0.7071068
#looks about right
pi - 3.2 #Indiana General Assembly bill #247, 1897.
sin.deg(45)
[1] 0.7173561
#oops ...
***
This email and any attachments are confidential. Any
use...{{dropped:8}}
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-
guide.html
and provide commented, minimal, self-contained, reproducible code.
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-
guide.html
and provide commented, minimal, self-contained, reproducible code.
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-
guide.html
and provide commented, minimal, self-contained, reproducible code.
--
Brian D. Ripley, rip...@stats.ox.ac.uk
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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[R] R Benchmarks
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 (ivo.we...@gmail.com) __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] use of formula in survey analysis with replicated weights
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 message. See example below, adapted from survey:withReplicates help page. library(survey) library(quantreg) data(api) ## one-stage cluster sample dclus1-svydesign( id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc) ## convert to bootstrap bclus1-as.svrepdesign( dclus1, type=bootstrap, replicates=100) ## median regression withReplicates( bclus1, quote( coef( rq( api00~api99, tau=0.5, weights=.weights theta SE (Intercept) 87.78505 18.850 api990.91589 0.028 # Defining formula outside Myformula - as.formula( api00~api99) # Rerun the same analysis withReplicates( bclus1, quote( coef( rq( formula= Myformula, tau=0.5, weights=.weights Erreur dans eval(expr, envir, enclos) : objet 'api00' introuvable # I suspect the evaluation not done in the right environment. #If you specify with data option in rq, the initial dataframe, formula is then correctly evaluated but .weights are not found. withReplicates( bclus1, quote( coef( rq( formula= Myformula, tau=0.5, weights=.weights, data=apiclus1 Erreur dans eval(expr, envir, enclos) : objet '.weights' introuvable Any help greatly appreciated Here is a workaround: Myformula - api00 ~ api99 withReplicates(bclus1, quote(coef(rq(formula(Myformula), tau=0.5, weights=.weights This solution makes sure the formula uses the environment where the weights are available. If you call as.formula() from outside the function, it will use the global environment. If you pass a character string, it will be converted to a formula object deep in a function and will thus use an environment where the weights are not be available either. Note that the same problem happens when using lm(). Regards O__ Alain Le Tertre c/ /'_ --- Institut de Veille Sanitaire (InVS)/ Département Santé Environnement (*) \(*) -- Responsable de l'unité Statistiques Outils ~~ - 12 rue du val d'Osne 94415 Saint Maurice cedex FRANCE Voice: 33 1 41 79 67 62 Fax: 33 1 41 79 67 68 email: a.leter...@invs.sante.fr __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Changing legend to fill colour in ggplot
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 2 2 $ species : Factor w/ 5 levels acinetobacter_sp,..: 2 5 1 4 3 2 5 1 4 3 $ genome_coverage_bp: int 8196 3405 8625 22568 2128 6100 1841 3914 8487 1064 $ genome_length : int 3571237 2541445 3912725 3479613 5460977 3571237 2541445 3912725 3479613 5460977 $ genome_coverage_percentage: Factor w/ 10 levels 0.02%,0.04%,..: 8 5 7 10 2 6 3 4 9 1 $ avg_depth_coverage: num 121.96 2.81 19.84 399.63 1.64 ... Now what I did is p=ggplot(df,aes(genome_coverage_percentage,avg_depth_coverage))+geom_point(aes(colour = species,shape = factor(id))) p+scale_shape_discrete(name =,labels=c(Patient 1, Patient 2)) That creats the plot below. But I want to change the circles of legend in fill colour. So that it doesn't look like it is only from Patient 1, as that also has circle. Can anybody help me please? You can change the default aesthetics displayed in the legend using the override.aes argument to guide_legend. scale_colour_discrete(guide=guide_legend(override.aes=aes(shape=15))) Also, when giving data, especially a data set this small, give the output of dput(df) as that gives the complete data in a format that can be used to recreate it exactly in someoneelse's session. If I had that, I would test this to make sure it looks right. Thanks a lot in advance :) Mitra -- Brian S. Diggs, PhD Senior Research Associate, Department of Surgery Oregon Health Science University __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] RE : use of formula in survey analysis with replicated weights
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 weights 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 message. See example below, adapted from survey:withReplicates help page. library(survey) library(quantreg) data(api) ## one-stage cluster sample dclus1-svydesign( id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc) ## convert to bootstrap bclus1-as.svrepdesign( dclus1, type=bootstrap, replicates=100) ## median regression withReplicates( bclus1, quote( coef( rq( api00~api99, tau=0.5, weights=.weights theta SE (Intercept) 87.78505 18.850 api990.91589 0.028 # Defining formula outside Myformula - as.formula( api00~api99) # Rerun the same analysis withReplicates( bclus1, quote( coef( rq( formula= Myformula, tau=0.5, weights=.weights Erreur dans eval(expr, envir, enclos) : objet 'api00' introuvable # I suspect the evaluation not done in the right environment. #If you specify with data option in rq, the initial dataframe, formula is then correctly evaluated but .weights are not found. withReplicates( bclus1, quote( coef( rq( formula= Myformula, tau=0.5, weights=.weights, data=apiclus1 Erreur dans eval(expr, envir, enclos) : objet '.weights' introuvable Any help greatly appreciated Here is a workaround: Myformula - api00 ~ api99 withReplicates(bclus1, quote(coef(rq(formula(Myformula), tau=0.5, weights=.weights This solution makes sure the formula uses the environment where the weights are available. If you call as.formula() from outside the function, it will use the global environment. If you pass a character string, it will be converted to a formula object deep in a function and will thus use an environment where the weights are not be available either. Note that the same problem happens when using lm(). Regards O__ Alain Le Tertre c/ /'_ --- Institut de Veille Sanitaire (InVS)/ Département Santé Environnement (*) \(*) -- Responsable de l'unité Statistiques Outils ~~ - 12 rue du val d'Osne 94415 Saint Maurice cedex FRANCE Voice: 33 1 41 79 67 62 Fax: 33 1 41 79 67 68 email: a.leter...@invs.sante.fr __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Transforming boolean subsetting into index subsetting
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 where the condition holds. Is there an easy way to transform the I vector into an indexes vector similar to: I == c(2,5,6) ? I know that I can traverse the I vector with a for() loop collecting the indexes, I just wonder if such an operation can be avoided. Thanks, -Sergio. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Transforming boolean subsetting into index subsetting
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 However, sometimes we are interested in the indexes of the elements where the condition holds. Is there an easy way to transform the I vector into an indexes vector similar to: I == c(2,5,6) ? I know that I can traverse the I vector with a for() loop collecting the indexes, I just wonder if such an operation can be avoided. which(I) -- Peter Dalgaard, Professor, Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Email: pd@cbs.dk Priv: pda...@gmail.com __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Transforming boolean subsetting into index subsetting
?which -- Bert On Fri, Jun 28, 2013 at 2:58 PM, Julio Sergio julioser...@gmail.com 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 However, sometimes we are interested in the indexes of the elements where the condition holds. Is there an easy way to transform the I vector into an indexes vector similar to: I == c(2,5,6) ? I know that I can traverse the I vector with a for() loop collecting the indexes, I just wonder if such an operation can be avoided. Thanks, -Sergio. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Transforming boolean subsetting into index subsetting
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(I) does add an extra twist - it considers missing values in I to be the same as FALSE's: seq_along(I)[ !is.na(I) I ] Bill Dunlap Spotfire, TIBCO Software wdunlap tibco.com -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Bert Gunter Sent: Friday, June 28, 2013 5:01 PM To: Julio Sergio Cc: r-h...@stat.math.ethz.ch Subject: Re: [R] Transforming boolean subsetting into index subsetting ?which -- Bert On Fri, Jun 28, 2013 at 2:58 PM, Julio Sergio julioser...@gmail.com 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 However, sometimes we are interested in the indexes of the elements where the condition holds. Is there an easy way to transform the I vector into an indexes vector similar to: I == c(2,5,6) ? I know that I can traverse the I vector with a for() loop collecting the indexes, I just wonder if such an operation can be avoided. Thanks, -Sergio. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb- biostatistics/pdb-ncb-home.htm __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Lexical scoping is not what I expect
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, Inf, etc.? I rather enjoy being able to set pi - 3 :-) cheers, Rolf Turner __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Lexical scoping is not what I expect
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 xieyi...@gmail.com
Phone: 206-667-4385 Web: http://yihui.name
Fred Hutchinson Cancer Research Center, Seattle
On Fri, Jun 28, 2013 at 6:30 PM, Rolf Turner rolf.tur...@xtra.co.nz wrote:
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, Inf, etc.?
I rather enjoy being able to set
pi - 3
:-)
cheers,
Rolf Turner
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Re: [R] Quantile Regression/(package (quantreg))
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 continuous variable For more help type ?summary.rms and ?Predict Frank When performing quantile regression (r package I used quantreg), the value of the quantile refers to the quantile value of the dependent variable. Typically when trying to predict, since the information we have are the independent variables, I am interested in trying to estimate the coefficients based on the quantile values of the independent variables' distribution. So that I can get an understanding, for certain ranges of the predictor/independent variable values, the (target/dependent variable) has (a certain level of exposure to the predictors)/(coefficients). Is there any way I can achieve that? Just in case, if I am incorrect about my understanding on the way quantiles are interpreted when using the package quantreg, please let me know. Thanks Mike -- Frank E Harrell Jr Professor and Chairman School of Medicine Department of Biostatistics Vanderbilt University __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
