Re: [R] C++11 requirements for package dependencies

package questions are usually better posted at r-package-devel Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Mon, Nov 30, 2020 at 12:45 AM Mark Clements

[R] C++11 requirements for package dependencies

A colleague uses a package I maintain (rstpm2) as a dependency in their package (rsimsum) with testing using GitHub Actions. They found that testing failed against R versions 3.3, 3.4 and 3.5 because recent versions of RcppArmadillo (which is a dependency in rstpm2) require C++11. As a dependency

Re: [R] C stack usage 7970372 is too close to the limit

Hello Raj, Please include a reproducible example. If you only give a generic error message, the best solution we can offer is to reboot your server and try it again. Anyway, from the information you gave, it seems like you should ask this question in the Rstudio community(I assume you are

Re: [R] C stack usage 7970372 is too close to the limit

Please take this discussion elsewhere... it is off-topic here. Ivan offered options earlier in this regard. On August 10, 2020 11:14:22 AM PDT, Raj kapoor wrote: >Hi John, > >Only the particular users getting error john. Please help me > > > > >On Mon, 10 Aug 2020, 11:43 pm Raj kapoor, >wrote:

Re: [R] C stack usage 7970372 is too close to the limit

Hi John, Only the particular users getting error john. Please help me On Mon, 10 Aug 2020, 11:43 pm Raj kapoor, wrote: > Hi John, > > I have 10 user in the instance, 9 user is working and access the R studio > app, but while access the 10th user it's getting stack usage limit issues, > then

Re: [R] C stack usage 7970372 is too close to the limit

Hi John, I have 10 user in the instance, 9 user is working and access the R studio app, but while access the 10th user it's getting stack usage limit issues, then we create the new users its working fine. On Mon, 10 Aug 2020, 10:21 pm John Harrold, wrote: > Hello Raj, > > I've gotten this type

Re: [R] C stack usage 7970372 is too close to the limit

Hello Raj, I've gotten this type of error in the past when I've done things like use while loops that didn't end. Basically, I think this means you're running out of memory. If you want more users, possibly increase the amount of ram in your machine. John On Mon, Aug 10, 2020 at 6:43 AM Raj

Re: [R] C stack usage 7970372 is too close to the limit

On Fri, 7 Aug 2020 22:25:32 +0530 Raj kapoor wrote: > I have one production instance in aws, in CentoOs linux environment, > i have 5 user to access the instance for using RStudio, In case > R-studio working 4 users running good, while we access 5th users its > getting error, Sorry, R-Studio

[R] C stack usage 7970372 is too close to the limit

Hi Team, I have one production instance in aws, in CentoOs linux environment, i have 5 user to access the instance for using RStudio, In case R-studio working 4 users running good, while we access 5th users its getting error, First issue : C stack usage 7970372 is too close to the limit Second

Re: [R] R C API resize matrice

Hi Morgan, In the example, please ignore `C_set_altrep_subset_method("compressedMatrix", get_subset_func)`. You do not have to define it to run the example. Best, Jiefei On Sat, Jun 15, 2019 at 11:45 AM King Jiefei wrote: > Hi Morgan, > > Thanks for the context, it seems like you want to

Re: [R] R C API resize matrice

Hi Morgan, Thanks for the context, it seems like you want to compress your matrix and you expect the "new" matrix should contain the same amount of information as the "old" one, it is correct? If this is the case, since you are using C++ code, a safer but imperfect solution is to find a C++ data

Re: [R] R C API resize matrice

Hi Jiedei, Thank you for your reply. To give you a bit more context, I wrote a function that find all the positions (index) of all small matrices inside a larger matrix. At the beginning I pre-allocate let's say a 100 by 2 matrix. However a lot of values might remain empty in this matrix of

Re: [R] R C API resize matrice

Hi, I don't think there is a native R API to do what you want here, but if the matrix is only used by you and not be exported to the other user, you can hack R data structure to achieve that goal. Because there is not too much context of your question, I will assume the whole point of resizing a

Re: [R] R C API resize matrice

Please do not re-post -- you have asked this before here. As this list is about R programming help, it is perhaps not surprising that you did not receive a reply. You might try R-devel instead where " Questions likely to prompt discussion unintelligible to non-programmers or topics that are too

[R] R C API resize matrice

Hi, Is there a way to resize a matrix defined as follows: SEXP a = PROTECT(allocMatrix(INTSXP, 10, 2)); int *pa = INTEGER(a) To row = 5 and col = 1 or do I have to allocate a second matrix "b" with pointer *pb and do a "for" loop to transfer the value of a to b? Thank you Best regards Morgan

[R] R C API Resize matrix

Hi, Is there a way to resize a matrix defined as follows: SEXP a = PROTECT(allocMatrix(INTSXP, 10, 2)); int *pa = INTEGER(a) To row = 5 and col = 1 or do I have to allocate a second matrix "b" with pointer *pb and do a "for" loop to transfer the value of a to b? Thank you Best regards Morgan

Re: [R] C/C++/Fortran Rolling Window Regressions

I looked into why the coefficients differ in Gabor's example and it's because the example mistakenly switched the order of x and y. The syntax is roll::roll_lm(x, y), which is the same as fastLm, but the example accidentally switched them. After correcting the example, the coefficients are all

Re: [R] C/C++/Fortran Rolling Window Regressions

> jeremiah rounds > on Thu, 21 Jul 2016 13:56:17 -0700 writes: > I appreciate the timing, so much so I changed the code to show the issue. > It is a problem of scale. > roll_lm probably has a heavy start-up cost but otherwise completely >

Re: [R] C/C++/Fortran Rolling Window Regressions

Hi Jeremiah: I think I wasn't that clear. I'm not suggesting the kalman filter to deal with time varying coefficients. As Roy pointed out, one can use the kalman filter to do regular regression where one "sees" a new data point as each time unit passes. It can be assumed that the coefficients do

Re: [R] C/C++/Fortran Rolling Window Regressions

This may be useful: Sven Hammarling and Craig Lucas "Updating the QR factorization and the least squares problem" http://eprints.ma.man.ac.uk/1192/01/covered/MIMS_ep2008_111.pdf http://www.maths.manchester.ac.uk/~clucas/updating/ 2016-07-21 20:02 GMT+02:00 jeremiah rounds

Re: [R] C/C++/Fortran Rolling Window Regressions

I agree that when appropriate Kalman Filter/Smoothing the higher-quality way to go about estimating a time-varying coefficient (given that is what they do), and I have noted that both the R package "dlm" and the function "StructTS" handle these problems quickly. I am working on that in parallel.

Re: [R] C/C++/Fortran Rolling Window Regressions

I have no idea which method produces the fastest results, but the package KFAS has a function to do recursive regressions using the Kalman filter. One difference is that it is not, as far as a I can telll, a moving window (so past data are being dropped), just a recursively computed

Re: [R] C/C++/Fortran Rolling Window Regressions

Hi Jermiah: another possibly faster way would be to use a kalman filtering framework. I forget the details but duncan and horne have a paper which shows how a regression can be re-computed each time a new data point is added .I forget if they handle taking one off of the back also which is what

Re: [R] C/C++/Fortran Rolling Window Regressions

I appreciate the timing, so much so I changed the code to show the issue. It is a problem of scale. roll_lm probably has a heavy start-up cost but otherwise completely out-performs those other versions at scale. I suspect you are timing the nearly constant time start-up cost in small data. I

Re: [R] C/C++/Fortran Rolling Window Regressions

I would be careful about making assumptions regarding what is faster. Performance tends to be nonintuitive. When I ran rollapply/lm, rollapply/fastLm and roll_lm on the example you provided rollapply/fastLm was three times faster than roll_lm. Of course this could change with data of different

Re: [R] C/C++/Fortran Rolling Window Regressions

Thanks all. roll::roll_lm was essentially what I wanted. I think maybe I would prefer it to have options to return a few more things, but it is the coefficients, and the remaining statistics you might want can be calculated fast enough from there. On Thu, Jul 21, 2016 at 12:36 PM, Achim

Re: [R] C/C++/Fortran Rolling Window Regressions

Jeremiah, for this purpose there are the "roll" and "RcppRoll" packages. Both use Rcpp and the former also provides rolling lm models. The latter has a generic interface that let's you define your own function. One thing to pay attention to, though, is the numerical reliability. Especially

Re: [R] C/C++/Fortran Rolling Window Regressions

Just replacing lm with a faster version would speed it up. Try lm.fit or even faster is fastLm in the RcppArmadillo package. On Thu, Jul 21, 2016 at 2:02 PM, jeremiah rounds wrote: > Hi, > > A not unusual task is performing a multiple regression in a rolling window >

[R] C/C++/Fortran Rolling Window Regressions

Hi, A not unusual task is performing a multiple regression in a rolling window on a time-series.A standard piece of advice for doing in R is something like the code that follows at the end of the email. I am currently using an "embed" variant of that code and that piece of advice is out

Re: [R] C stack error in as.vector() starting in R 3.3.0

Luke, Thanks for this point out. I started removing packages one-by-one in R v.3.3.1. Oddly enough, it went away after I removed the Matrix package. When I restarted R, the same version of Matrix (1.2-6) had been "reinstalled" (?), but now no C stack error. Lets see if the others that were having

Re: [R] C stack error in as.vector() starting in R 3.3.0

I cannot reproduce this. My best guess is that there is a problem, maybe a version incompatibility, with one of the packages loaded when load("problem.method.rdata"). This includes adegenet apex copula Rcpp DBI sp colorspace and any dependencies these are bringing in. Best, luke On Fri, 1

[R] C stack error in as.vector() starting in R 3.3.0

Apologies for the long post. This is an issue I have been struggling with and I have tried to be as complete, to the point, and reproducible as possible. In documenting a package with roxygen2, I have come across an error that does not occur in R 3.2.4 revised, but does occur in R 3.3.0 and

Re: [R] c(1:n, 1:(n-1), 1:(n-2), ... , 1)

Hi I have to correct myself, this last solution is not universally valid here a better one: tmp1 <- ( 1 - outer( max( x):1, x, FUN='-')) tmp1[ tmp1 > 0] On 2015-09-17 21:06:30, Frank Schwidom wrote: > > how abount a more complicated one? > > outer( 1:5, 1:5, '-')[ outer( 1:5, 1:5, '>')] >

Re: [R] c(1:n, 1:(n-1), 1:(n-2), ... , 1)

On Thu, 17 Sep 2015, Peter Langfelder wrote: Not sure if this is slicker or easier to follow than your solution, but it is shorter :) do.call(c, lapply(n:1, function(n1) 1:n1)) Also not sure about efficiency but somewhat shorter... unlist(lapply(5:1, seq)) Peter On Thu, Sep 17, 2015 at

Re: [R] c(1:n, 1:(n-1), 1:(n-2), ... , 1)

Not sure if this is slicker or easier to follow than your solution, but it is shorter :) do.call(c, lapply(n:1, function(n1) 1:n1)) Peter On Thu, Sep 17, 2015 at 11:19 AM, Dan D wrote: > Can anyone think of a slick way to create an array that looks like c(1:n, > 1:(n-1),

Re: [R] c(1:n, 1:(n-1), 1:(n-2), ... , 1)

sequence( 5:1) Regards. On Thu, Sep 17, 2015 at 11:19:05AM -0700, Dan D wrote: > Can anyone think of a slick way to create an array that looks like c(1:n, > 1:(n-1), 1:(n-2), ... , 1)? > > The following works, but it's inefficient and a little hard to follow: > n<-5 >

Re: [R] c(1:n, 1:(n-1), 1:(n-2), ... , 1)

I'm not too sure this is any better: n<-5 c<-0; # establish result as numeric for(i in seq(n,1,-1)){ c<-c(c,seq(1,i)); str(c); }; #generate array c<-c[2:length(c)]; #remove the leading 0 If you're a fan of recursive programming: > mklist <- function(x) { if (x==1) return(1) else return(

[R] c(1:n, 1:(n-1), 1:(n-2), ... , 1)

Can anyone think of a slick way to create an array that looks like c(1:n, 1:(n-1), 1:(n-2), ... , 1)? The following works, but it's inefficient and a little hard to follow: n<-5 junk<-array(1:n,dim=c(n,n)) junk[((lower.tri(t(junk),diag=T)))[n:1,]] Any help would be greatly appreciated! -Dan

Re: [R] c(1:n, 1:(n-1), 1:(n-2), ... , 1)

You can add this to the list of options to be tested, although my bet would be placed on `sequence(5:1)`: > Reduce( function(x,y){c( 1:y, x)}, 1:5) [1] 1 2 3 4 5 1 2 3 4 1 2 3 1 2 1 On Sep 17, 2015, at 11:40 AM, Achim Zeileis wrote: > On Thu, 17 Sep 2015, Peter Langfelder wrote: > >> Not

Re: [R] c(1:n, 1:(n-1), 1:(n-2), ... , 1)

how abount a more complicated one? outer( 1:5, 1:5, '-')[ outer( 1:5, 1:5, '>')] [1] 1 2 3 4 1 2 3 1 2 1 On Thu, Sep 17, 2015 at 11:52:27AM -0700, David Winsemius wrote: > You can add this to the list of options to be tested, although my bet would > be placed on `sequence(5:1)`: > > >

Re: [R] c(1:n, 1:(n-1), 1:(n-2), ... , 1)

Note that: >> Also not sure about efficiency but somewhat shorter... >> unlist(lapply(5:1, seq)) >> >>> Peter >>> is almost exactly sequence(5:1) which is unlist(lapply(5:1,seq_len)) which is "must preferred". See ?seq for details Cheers, Bert >>> On Thu, Sep 17, 2015 at 11:19 AM, Dan D

Re: [R] c(1:n, 1:(n-1), 1:(n-2), ... , 1)

Very nice variety of solutions to create c(1:n, 1:(n-1), 1:(n-2), ... , 1) #Testing the methods with n=1000 (microbenchmark) n<-1000 # by far the nicest-looking, easiest to follow, and fastest is Frank Schwidom's: # it also requires the minimum amount of memory (as do several of the others) #

Re: [R] c(1:n, 1:(n-1), 1:(n-2), ... , 1)

If you are interested in speed for long input vectors try the following, which should give the same result as sequence(). mySequence <-function (nvec) { nvec <- as.integer(nvec) seq_len(sum(nvec)) - rep(cumsum(c(0L, nvec[-length(nvec)])), nvec) } E.g., > n <- rpois(1e6, 3) >

Re: [R] C compilation error (unknown type R_xlen_t) when installing Rmpi package

Support for long vectors (and hence R_xlen_t) was introduced in R 3.0.0. Your version is far outdated. If you wait a teeny but longer (after April 16) to update, you'll get R 3.2.0. Henrik On Apr 8, 2015 08:00, Sebastian L sl-resea...@outlook.com wrote: Hi, I am trying to use the parallel

Re: [R] C compilation error (unknown type R_xlen_t) when installing Rmpi package

On 08/04/2015 16:00, Sebastian L wrote: Hi, I am trying to use the parallel computing cluster of our university. To that end, I would like to install the Rmpi package on the cluster. The R version currently installed on the cluster is This was a matter for the R-devel list as it involves

[R] C compilation error (unknown type R_xlen_t) when installing Rmpi package

Hi, I am trying to use the parallel computing cluster of our university. To that end, I would like to install the Rmpi package on the cluster. The R version currently installed on the cluster is R version 2.15.2 (2012-10-26) -- Trick or Treat Platform: x86_64-redhat-linux-gnu (64-bit) I am

[R] C#

I will keep this short as this might be the wrong list: I have found one (beta) project that allows R to interface with C#. Are there others? Any favorites. Best, KW __ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see

[R] C project within R function

Hi all, I need some assistance regarding the use of C project (set of programming files) as R functions in Windows OS. By now I really would like to avoid package-building. What are the steps to undergo or where can I check to perform that successfully? Thanks in advance, My best

Re: [R] C project within R function

On 21/11/2014, 3:02 PM, Diogo André Alagador wrote: Hi all, I need some assistance regarding the use of C project (set of programming files) as R functions in Windows OS. By now I really would like to avoid package-building. What are the steps to undergo or where can I check to

Re: [R] C project within R function

Diogo, For a gentle introduction to package creation see Hadley Wickham's book in progress on the subject at http://r-pkgs.had.co.nz. This site is particularly accessible if you use RStudio, but is not dependent on its use. I use very simple packages that are not designed to be used by others

[R] c() and dates

I'm a bit puzzled by a certain behavior with dates. (R version 3.1.1) temp1 - as.Date(1:2, origin=2000/5/3) temp1 [1] 2000-05-04 2000-05-05 temp2 - as.POSIXct(temp1) temp2 [1] 2000-05-03 19:00:00 CDT 2000-05-04 19:00:00 CDT So far so good. On 5/4, midnight in Greenwich it was 19:00 on

Re: [R] c() and dates

On Oct 3, 2014, at 7:19 AM, Therneau, Terry M., Ph.D. wrote: I'm a bit puzzled by a certain behavior with dates. (R version 3.1.1) temp1 - as.Date(1:2, origin=2000/5/3) temp1 [1] 2000-05-04 2000-05-05 temp2 - as.POSIXct(temp1) temp2 [1] 2000-05-03 19:00:00 CDT 2000-05-04 19:00:00

Re: [R] c() and dates

On Oct 3, 2014, at 7:19 AM, Therneau, Terry M., Ph.D. wrote: I'm a bit puzzled by a certain behavior with dates. (R version 3.1.1) temp1 - as.Date(1:2, origin=2000/5/3) temp1 [1] 2000-05-04 2000-05-05 temp2 - as.POSIXct(temp1) temp2 [1] 2000-05-03 19:00:00 CDT 2000-05-04 19:00:00

Re: [R] c() and dates

Well duh -- type c.Date at the command prompt to see what is going on. I suspected I was being dense. Now that the behaior is clear can I follow up on David W's comment that redfining the c.Date function as structure(c(unlist(lapply(list(...), as.Date))), class = Date) allows for a

[R] .C and .Fortran

Hi, I'd like to know what is the difference between the functions .C() and .Fortran. I noticed that by enclosing my F90 subroutines in modules .Fortran() can't find them any more in the load table, while .C() still can. I also checked that the subroutine was loaded with the is.loaded()

Re: [R] .C and .Fortran

On 03/09/2014 13:28, Filippo Monari wrote: Hi, I'd like to know what is the difference between the functions .C() and .Fortran. I noticed that by enclosing my F90 subroutines in modules .Fortran() can't find them any more in the load table, while .C() still can. I also checked that the

Re: [R] c() with POSIXlt objects and their timezone is lost

On 23.06.2014 23:52, Marc Girondot wrote: When two POSIXlt objects are combine with c(), they lost their tzone attribute, even if they are the same. I don't know if it is a feature, but I don't like it ! Marc es - strptime(2010-02-03 10:20:30, format=%Y-%m-%d %H:%M:%S, tz=UTC) es [1]

Re: [R] c() with POSIXlt objects and their timezone is lost

This is a rope. Don't push it. Been there, been swatted. The current structure of R cannot support vectors of POSIXt timestamps that have different tzones in different elements. You can keep a parallel vector of tzones separately and manage environment variable TZ as needed if you really must

[R] c() with POSIXlt objects and their timezone is lost

When two POSIXlt objects are combine with c(), they lost their tzone attribute, even if they are the same. I don't know if it is a feature, but I don't like it ! Marc es - strptime(2010-02-03 10:20:30, format=%Y-%m-%d %H:%M:%S, tz=UTC) es [1] 2010-02-03 10:20:30 UTC attributes(es) $names

Re: [R] C: drive memory full

-4352 -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of jwd Sent: Tuesday, June 17, 2014 8:10 PM To: r-help@r-project.org Subject: Re: [R] C: drive memory full On Tue, 17 Jun 2014 12:48:54 + Hiyoshi, Ayako ayako.hiyoshi

Re: [R] C: drive memory full

-project.org Subject: Re: [R] C: drive memory full On Tue, 17 Jun 2014 12:48:54 + Hiyoshi, Ayako ayako.hiyoshi...@alumni.ucl.ac.uk wrote: Dear Martyn and Professor Ripley, Thank you so much for your help. I used Window's large file search (it was useful! thank you

Re: [R] C: drive memory full

To: David L Carlson Cc: r-help@r-project.org Subject: Re: [R] C: drive memory full One program that I have found valuable in looking at the size of files on disk is SequoiaView. It creates a 'treemap' of the sizes of the files and lets you zoom in to specific directories and such. Jim Holtman Data

[R] C: drive memory full

Dear R users, Hello, I am new to R and confused about my PC's memory space after using R a while. My PC is Windows 8, RAM 8GB. I have run some analyses using commands like vglm, aalen(Sruv()), lm()... some regressions. I also use Stata, and when I tried to run Stata (big file), Stata

Re: [R] C: drive memory full

tempdir() is specific to an R session. Start up R and run dirname(tempdir()) and look at that directory. Shut down R, then remove all old files/folders in that directory, especially those beginning with 'Rtmp'. An R process tries to clean up after itself but - it cannot do so if it

Re: [R] C: drive memory full

10:37 To: Hiyoshi, Ayako; r-help@R-project.org Subject: Re: [R] C: drive memory full tempdir() is specific to an R session. Start up R and run dirname(tempdir()) and look at that directory. Shut down R, then remove all old files/folders in that directory, especially those beginning with 'Rtmp

Re: [R] C: drive memory full

Ripley; r-help@R-project.org Subject: Re: [R] C: drive memory full Dear Professor Ripley, Thank you so much for your quick reply. I tried 'dianame(tempdir())' and removed several 'Rtemp' and all other files. Unfortunately it did not changed C: drive space much. I am really sorry, but could

Re: [R] C: drive memory full

IT support, but they could not spot either. Kind regards, Ayako From: Prof Brian Ripley rip...@stats.ox.ac.uk Sent: 17 June 2014 10:37 To: Hiyoshi, Ayako; r-help@R-project.org Subject: Re: [R] C: drive memory full tempdir() is specific to an R session

Re: [R] C: drive memory full

From: Martyn Byng martyn.b...@nag.co.uk Sent: 17 June 2014 12:10 To: Hiyoshi, Ayako; Prof Brian Ripley; r-help@R-project.org Subject: RE: [R] C: drive memory full Hi, Try http://social.technet.microsoft.com/wiki/contents/articles/19295.windows-8-how-to-search-for-large

Re: [R] C: drive memory full

, Ayako; Prof Brian Ripley; r-help@R-project.org Subject: RE: [R] C: drive memory full Hi, Try http://social.technet.microsoft.com/wiki/contents/articles/19295.windows-8-how -to-search-for-large-files.aspx Martyn -Original Message- From: r-help-boun...@r-project.org [mailto:r

Re: [R] C: drive memory full

On Tue, 17 Jun 2014 12:48:54 + Hiyoshi, Ayako ayako.hiyoshi...@alumni.ucl.ac.uk wrote: Dear Martyn and Professor Ripley, Thank you so much for your help. I used Window's large file search (it was useful! thank you), but there is no big files detected in C: drive . Perhaps I will have to

Re: [R] Plotting issues with -par(mfrow=c(r,c))- after -boot-

On 1 June 2014 22:07, Jeff Newmiller jdnew...@dcn.davis.ca.us wrote: Read ?plot.boot, in particular the Side Effects section. Not a very friendly function... you will have to modify it if you wish to proceed. I guess you were expecting me to come back at some stage to say that I'd figured out

Re: [R] Plotting issues with -par(mfrow=c(r,c))- after -boot-

No, because I have never used Boot, or tried to use plot.boot... I just know that there are three main styles of plotting in R and the manual pages are usually informative on which is in use. I am glad you figured out a better solution though, and thanks for reporting back.

Re: [R] Plotting issues with -par(mfrow=c(r,c))- after -boot-

On 1 June 2014 22:07, Jeff Newmiller jdnew...@dcn.davis.ca.us wrote: Read ?plot.boot, in particular the Side Effects section. Not a very friendly function... you will have to modify it if you wish to proceed. Thank you. I shall check this out later and may return with queries, but only if

Re: [R] Plotting issues with -par(mfrow=c(r,c))- after -boot-

having difficulties getting -par(mfrow=c(r,c))- to work as it should after running bootstrapped regression models using -boot-. An example (tested): test=data.frame(A=rnorm(500, mean=2.72, sd=5.36), B=sample(c(12,20,24,28,32),size=500,prob=c(0.333,0.026,0.026,0.436,0.179),replace=TRUE), C

[R] Plotting issues with -par(mfrow=c(r,c))- after -boot-

R 3.1.0 / RStudio 0.98.507 / OpenSUSE Linux 13.1 I'm having difficulties getting -par(mfrow=c(r,c))- to work as it should after running bootstrapped regression models using -boot-. An example (tested): test=data.frame(A=rnorm(500, mean=2.72, sd=5.36), B=sample(c(12,20,24,28,32),size=500,prob=c

Re: [R] Plotting issues with -par(mfrow=c(r,c))- after -boot-

--- Sent from my phone. Please excuse my brevity. On June 1, 2014 1:20:45 PM PDT, Clive Nicholas cliveli...@googlemail.com wrote: R 3.1.0 / RStudio 0.98.507 / OpenSUSE Linux 13.1 I'm having difficulties getting -par(mfrow=c(r,c

[R] C Interface in R

Dear R Users--- I spent some time implementing the AS75 WLS regression algorithm in C in order to learn the R interface to C. I did not find an easy, brief C+R example of an algorithm that used persistent storage across calls. they probably exist, but I could not find a nice brief template for

[R] C symbol name psmirnov2x not in load table

I'm working with some old code that worked under R 2.15.3 but gives an error under 3.0.0 and 3.0.1 : 1.0 - .C(psmirnov2x, p = as.double(10.0), as.integer(1000), as.integer(1000))$p Error in .C(psmirnov2x, p = as.double(10), as.integer(1000), as.integer(1000)) : C symbol name psmirnov2x not

[R] c(), rbind and cbind functions - why type of resulting object is double

Hello Everyone, I am using R 2.15.0 and I came across this behaviour and I was wondering why I don't get an integer vector or and integer matrix with the following code: z - c(1, 2:0, 3, 4:8) typeof(z) [1] double z - rbind(1, 2:0, 3, 4:8) Warning message: In rbind(1, 2:0, 3, 4:8) :

Re: [R] c(), rbind and cbind functions - why type of resulting object is double

-help-boun...@r-project.org] On Behalf Of Lourdes Peña Castillo Sent: Tuesday, January 22, 2013 9:26 AM To: r-help@r-project.org Subject: [R] c(), rbind and cbind functions - why type of resulting object is double Hello Everyone, I am using R 2.15.0 and I came across this behaviour

Re: [R] c(), rbind and cbind functions - why type of resulting object is double

To: r-help@r-project.org Subject: [R] c(), rbind and cbind functions - why type of resulting object is double Hello Everyone, I am using R 2.15.0 and I came across this behaviour and I was wondering why I don't get an integer vector or and integer matrix with the following code: z - c(1, 2:0, 3, 4

[R] c weirdness

is there a way to avoid c() appending .0 and .1 to seed? --8---cut here---start-8--- c(nons=1, seed=3) nons seed ## good! 13 c(nons=1, seed=tab[1]) nons seed.0 ## don't want .0! 1 2344600 c(nons=1,

Re: [R] c weirdness

On 07/11/2012 3:53 PM, Sam Steingold wrote: is there a way to avoid c() appending .0 and .1 to seed? Don't give it a named vector. You can use the unname() function to strip the names from tab: c(nons=1, seed=unname(tab[1])) --8---cut here---start-8---

Re: [R] c weirdness

-Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Sam Steingold Sent: Wednesday, November 07, 2012 12:53 PM To: r-help@r-project.org Subject: [R] c weirdness is there a way to avoid c() appending .0 and .1 to seed? --8

Re: [R] c weirdness

Dunlap Spotfire, TIBCO Software wdunlap tibco.com -Original Message- From: William Dunlap Sent: Wednesday, November 07, 2012 1:24 PM To: 's...@gnu.org'; r-help@r-project.org Subject: RE: [R] c weirdness Your example doesn't work here - you didn't show what 'tab' was. Perhaps

[R] R/C++ interfaces: crashes when using .c(), followed by correct results when R restarted

Dear all I have written a function in C++ , equil_distC, that I am calling from an R script. In the last few days, R has repeatedly crashed when calling this function, or delivered obviously wrong outputs. However, when I restarted R after the crash, the results turned out to be OK most of

Re: [R] R/C++ interfaces: crashes when using .c(), followed by correct results when R restarted

First, the posting guide asks you to send questions about compiled code to the R-devel list. These are all classic symptoms of the use of uninitialized variables or writing out of bounds, but of which you can catch by using valgrind: see 'Writing R Extensions'. They are much harder to find

Re: [R] c(a, b) for POSIXct objects with tzone attributes?

Hi, Prof. Ripley, Bert: Thanks for the comments. Might there be a function similar to c but retains more attributes than just names? Before I write such, I felt a need to ask if anyone knows where it may already have been done -- and if people have suggestions for how

Re: [R] c(a, b) for POSIXct objects with tzone attributes?

Spencer: Just for fun, may I hazard a guess: It would be messy to retain time zones if your were concatenating objects with more than one time zone among them. Normalizing everything to a single zone probably also makes subsequent operations on the results much easier. Not that it couldn't be

Re: [R] c(a, b) for POSIXct objects with tzone attributes?

On 09/07/2012 07:12, Bert Gunter wrote: Spencer: Just for fun, may I hazard a guess: It would be messy to retain time zones if your were concatenating objects with more than one time zone among them. Actually, impossible as the design allows for only one timezone for each object.

[R] c(a, b) for POSIXct objects with tzone attributes?

Hello: What is the recommended method for retaining the tzone attributes when concatonating POSIXct objects? (d1 - ISOdate(1970,1,1)) # Sets the tzone attribute = GMT [1] 1970-01-01 12:00:00 GMT (d1.2 - c(d1, d1)) # c(..) strips the tzone attribute, displays in the time zone of

[R] C++ and R

Hello: I have some C++ code and I want to know if it is ok to load it into R using .Call. Also, what's the difference between using Rdefines.h or Rinternals.h headers? It is just in the used macros? I've been reading Writing R Extensions but I'm a bit confused. Thanks,

[R] R/C++ interfaces: documentation for SET_STRING_ELT, PROTECT, etc...

Dear all, I am reading C++ code that is called in an R package. It is not clear to me what SET_STRING_ELT, getAttrib, etc exactly do. I understand that these are macros that have been declared in Rinternals.h and who are used for the correct translation of the R data structures, but I have

[R] c() in Mac does not work

I recently changed to Mac OS X 10.7.3 from Windows and this simple function is giving errors. c(4,7,7) Error in c(4, 7, 7) : unused argument(s) (7) c(1,7:9) Error in d[i, ] : incorrect number of dimensions c(1:5, 10.5, next) Error in c(1:5, 10.5, next) : unused argument(s) (next) c(1,2)

Re: [R] c() in Mac does not work

Hi, My best guess is that the c() you want to be calling is not the c() you are calling. This can happen if it is masked by a function definition in you global environment or in a package you load. What happens when you type: c at the console? Also, from one of your sessions where it , c(),

Re: [R] c() in Mac does not work

My guess is that somewhere you've accidentally redefined c to be another function. Try this: Open the Terminal and type R --vanilla this will start R totally clean and then try c(4,7,7) c(1, 7:9) I bet your issues go away. If that's the case, you can probably fix things by clearing your old

Re: [R] c() in Mac does not work

almost certainly you restored an old workspace with a conflicting definition of the c function. type c to confirm, also type conflicts(detail=TRUE) The repair is to remove the conflicting definition rm(c) The long term solution is to adopt the recommended practice of not saving your

[R] C

Sent from my iPod __ 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] C-side: Applying a function (given as param) to data (given as param)

Hello, I'm implementing a package (C-extension), where one function gets data and a function that needs to be applied to the data. I want to apply the function to (parts of) the data on the C-side. 1) how do I apply a function (given via SEXP) to data 2) how do I select parts of the data?

[R] C source code question (Robustbase edition)

Hi all, I have been trying to add the line: h = n - p0 + 1; just after h = n / 2 + 1; (line 131) in the source code (the original paper mention this is possible for p0lt;n). with p0 declared as an int (actually i used the same declaration protocol as n everywhere in the code). The

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