similar to: difficulty with 'parallel' in building r57032 -- missing Makefile?

Trying to install latest rjags (3-5) from CRAN with JAGS 3.2.0 installed on Ubuntu 10.04, with r-devel ... the bottom line is that it fails while loading with /libs/rjags.so: undefined symbol: _ZN7Console15checkAdaptationERb Has anyone else seen this or is it a glitch somewhere in my system? thanks Ben Bolker ================== bolker at ubuntu-10-new:~/R/pkgs/rjags$ jags Welcome to

Hi All, How can I get the expected value from a discrete cdf? Is there any R function that can do this? Thanks, Annie [[alternative HTML version deleted]]

My statistics teacher wrote a textbook and included .rdata files for the problem set data. I downloaded these and opened one of them up. Then I used the ls() command, and it gave me this: > ls() [1] "ex02-12" However, when i try to use the object, it interprets it as ex02 - 12, and I get the following error: > ex02-12 Error: object 'ex02' not found I don't know why

There seems to be a latent flaw in the definition of struct SEXPREC in Rinternals.h, which likely doesn't cause problems now, but could if the relative sizes of data types changes. The SEXPREC structure contains a union that includes a primsxp, symsxp, etc, but not a vecsxp. However, in allocVector in memory.c, zero-length vectors are allocated using allocSExpNonCons, which appears to

I'm sure I'm being an absolute bonehead (again), but can someone suggest what I might be doing wrong? Trying to build latest r-devel on Ubuntu 10.04; as recommended in various places, trying to build it in a separate build directory (since starting to compose this e-mail I've found that it works if I build in the original source directory [as disrecommended], so this has become a

Dear List, i would like to mimic the behaviour or the following indexing with a do.call construct to be able to supply the arguments to `[` as a list: test = matrix[1:4,2] result = test[2,] My try, however, did not work: result = do.call(`[`,list(test,2,NULL)) result = do.call(`[`,list(test,2,)) result = do.call(`[`,list(test,2,'')) How can I use the do.call in that way with

Dear colleagues, I have a data set that looks roughly like this; mydat<-data.frame(state=c(rep("Alabama", 5), rep("Delaware", 5), rep("California", 5)), news=runif(15, min=0, max=8), cum.news=rep(0, 15)) For each state, I'd like to cumulatively sum the value of "news" and make that put that value in cum.news. I'm trying as follows but I get

Hi! Just wondering if anyone has this working ... Centos-7 guest in VMware-10 host (on Windows-7 :-( ) Out of the box, shared folders and drag&drop do not work although X screen resolution sensing is fine (ie xrandr reports the resolution of the host screen as well as the peculiar screen options built-in) and I can Alt-Enter to full screen quite happily. I tried Fedora-22 too but did

I have the following results for an ANOVA comparing two nested models. I wasn't sure how I am supposed to report this result in the area of psychology. Specifically, am I supposed to report the DF's or just the F ratio? I could manually calculate the degrees of freedoms, but there must be a reason why R does not give this information, i.e. those are not conventionally used in the

Hi, I've data from an incomplete fatorial design. One level of a factor doesn't has the levels of the other. When I use lm(), the summary() return NA for that non estimable parameters. Ok, I understant it. But I use contrast::contrast(), gmodels::estimable(), multcomp::glht() and all these fail when model has NA estimates. This is becouse vcov() and coef() has different dimensions. Is

Dear all, I am trying to aggregate a table (divided in two lists here), but get a memory error. Here is the code I'm running : sessionInfo() print(paste("memory.limit() ", memory.limit())) print(paste("memory.size() ", memory.size())) print(paste("memory.size(TRUE) ", memory.size(TRUE))) print(paste("size listX ", object.size(listX)))

Hi, sorry for repeating the question but this is kind of important to me and i don't know whom should i ask. So as noted before when I do a parameter fit to the beta distr i get: fitdist(vectNorm,"beta"); Fitting of the distribution ' beta ' by maximum likelihood Parameters: estimate Std. Error shape1 2.148779 0.1458042 shape2 810.067515 61.8608126 Warning

Why does R think these numbers ***are*** equal? In a somewhat bizarre set of circumstances I calculated x0 <- 0.03580067 x1 <- 0.03474075 y0 <- 0.4918823 y1 <- 0.4474461 dx <- x1 - x0 dy <- y1 - y0 xx <- (x0 + x1)/2 yy <- (y0 + y1)/2 chk <- yy*dx - xx*dy + x0*dy - y0*dx If you think about it ***very*** carefully ( :-) )

dear all, i have a quite simple question, i want to fill up a Matrix like done in the following function, but the performance is very bad for large dimensions is there a way to do this like with apply or something similar? makeMatrix <- function(a, b,dim) { X=matrix(0,ncol=dim,nrow=dim) for (i in c(1:dim)){ for (j in c(1:dim)) { if (i==j) {X[i,j]<-a} else { X[i,j]<- exp((

Hi, all. I'm new to R. I've been a SAS programmer for 20 years. I seem to be having trouble with the most basic task - bringing a table in an *.RData file into a data.frame object. Here's how I created the *.RData file. library(RODBC) db <- odbcConnect("*******") df <- sqlQuery( db , "select * from schema.table where year(someDate)=2006" ) save(

Hello, I was wondering if someone knows the formula used by the function lm to compute the t-values. I am trying to implement a linear regression myself. Assuming that I have K variables, and N observations, the formula I am using is: For the k-th variable, t-value= b_k/sigma_k With b_k is the coefficient for the k-th variable, and sigma_k =(t(x) x )^(-1) _kk is its standard deviation.

I wouldn't be at all surprised if I turned out to be doing something boneheaded, but I've *tried* to follow all the relevant rules ... Based on a clean SVN checkout of R-devel r61617, building in a separate directory, I end up with Error in eval(expr, envir, enclos) : object '.print.via.format' not found Has anyone encountered this or does anyone have any further

Dear R-helpers, In the following example I compute ret and returns the SAME way. In ret I use compute returns for EACH column and in returns I do it for the whole data frame. Could someone please tell me why I see a lagged result,by which I mean ret and returns are different by one lag. getSymbols("GOOG",src="yahoo") ret<-apply(GOOG,2,function(x) diff(log(x)) / lag(x,1) )

try modprobe vmhgfs -- Eero 2015-08-07 6:53 GMT+03:00 Bob Hepple <bob.hepple at gmail.com>: > Bob Hepple <bob.hepple at ...> writes: > > > It's the shared folder that I would really like to get working. vmware- > > hgfsclient reports my share but there is no /mnt/hgfs directory. Also > > 'lsmod|grep hgfs' reports nothing. > > > > also:

Try this: fn <- "tmp.dat" x <- 1:3 dump("x",file=fn) file.info(fn) ## 9 bytes file.copy(paste("./",fn,sep=""),fn,overwrite=TRUE) file.info(fn) ## 0 bytes (!!) Normally file.copy() checks and disallows overwriting a file with itself, but it only checks whether character string 'from' is the same as character string 'to'