search for: ndims

Hi, is there a function in R already doing what I try to do below: # Let 'x' be an array with *any* number of dimensions (>=1). x <- array(1:24, dim=c(2,2,3,2)) ... x <- array(1:24, dim=c(4,3,2)) i <- 2:3 ndim <- length(dim(x)) if (ndim == 1) y <- x[i] else if (ndim == 2) y <- x[i,] else if (ndim == 3) y <- x[i,,] else ... and so on. My current

R-listers, In using the adapt function, I am getting the following warning: Ifail=2, lenwrk was too small. -- fix adapt() ! Check the returned relerr! in: adapt(ndim = 2, lower = lower.limit, upper = upper.limit, functn = pr.set, Would someone explain what the 'lenwrk' value indicates in order to help diagnose this issue. Also, what are the possible codes for Ifail, so I can set

Dear R developers, While improving duplicated.array() and friends and developing equivalents for the new ff package for large datasets I came across two questions: 1) is it safe to use duplicated.default(), unique.default() and match() on arbitrary lists? If so, we can speed up duplicated.array and friends considerably by using list() instead of paste(collapse="\r") 2) while

Hi all I do not understand why I am getting the following error message. Can anybody help me with this? Thanks in advance. install.packages("cmprsk") library(cmprsk) result1 <-crr(ftime, fstatus, cov1, failcode=1, cencode=0 ) one.pout1 = predict(result1,cov1,X=cbind(1,one.z1,one.z2)) predict.crr(result1,cov1,X=cbind(1,one.z1,one.z2)) Error: could not find function

I want to call dll from R but encounter problem in compiling the fortran program. First I try "Rcmd shlib prog.f", it failed and warning: make[1]: `libR.a' is up to date. make: *** No rule to make target `'prog.o', needed by `prog.a'. stop. Then I try to compile it by absoft fortran compiler, it works and produces prog.dll. But when this routine is called in R, it

Is it just my installation or bug in 1.9.0 ? The same thing works fine in 1.8.1 Best regards, Ryszard # R-1.9.0 library(pls.pcr) nr <- 8; ndim <- 2 x <- matrix(rnorm(nr*ndim), nrow=nr) y <- as.matrix(x[,1]) for (i in 2:ndim) y <- y + x[,i] y <- y + rnorm(length(y)) m <- pls(x,y,validation='CV') # Error in paste(ncomp, "LV's") : Argument

I was wondering if it is possible to do the following in a smarter way. I want get the mean value across the columns of a matrix, but I want to do this on subrows of the matrix, given by some vector(same length as the the number of rows). Something like nObs<- 6 nDim <- 4 m <- matrix(rnorm(nObs*nDim),ncol=nDim) fac<-sample(1:(nObs/2),nObs,rep=T) ##loop trough different

...t(global.emis.mx), > + start=c(1, 1, 1), > + count=c(-1,-1, 1)) # -1 -> all data When I try to *pull* the data *from* the netCDF I created, > > target.data <- ncvar_get( > + nc=netcdf.file, > + varid=emis.var, > + # read all the data > + start=rep(1, emis.var$ndims), > + # count=rep(-1, emis.var$ndims)) I get > Error in if (nc$var[[li]]$hasAddOffset) addOffset = nc$var[[li]]$addOffset else addOffset = 0 : > argument is of length zero And I get the same error if I try the minor variation(s) > target.data <- ncvar_get( + nc=netcdf.file,...

Hello, I am trying to call a FORTRAN subroutine from R. The Fortran code is @: http://lib.stat.cmu.edu/apstat/206 It performs a bivariate isotonic regression on a rectangular grid (m X n) matrix. I used the g77 compiler and successfully created a dll file and it also loads successfully from R. But somehow the programs fails to run properly. (I do get the correct result when I compile the

Dear All, I am struggling with the following problem: I am given a NxN symmetric matrix P ( P[i,i]=0, i=1...N and P[i,j]>0 for i!=j) which stands for the relative distances of N points. I would like use it to get the coordinates of the N points in a 2D plane. Of course, the solution is not unique (given one solution, I can translate or rotate all the points by the same amount and generate

How to programmatically (i.e., without no or minimal handcoding) copy a netCDF file? (Without calling > system("cp whatever wherever") :-) Why I ask: I need to "do surgery" on a large netCDF file (technically an I/O API file which uses netCDF). My group believes a data-assimilation error caused a data variable to be corrupted in a certain way, so I'm going to

...excel is 16383, this cvs file doesn't show all data. Obviously, I need to transpose the matrix.. I tried to use transpose function but failed. > bbb=t(data2) Error in t.default(data2) : argument is not a matrix > ccc=t(hyo) > ccc [1] "file has dimensions:" Error in if (nc$ndims > 0) for (i in 1:nc$ndims) { : argument is of length zero Teach me how to deal with this problem. Thank you very much. -Hyo [[alternative HTML version deleted]]

Hi all I was wondering if someone could help me. I have to estimate some parameters, so I am using the function nlm. Inside this function I have to integrate, hence I am using the function adapt. I don't understand why it is giving the following warnings: At the beginning: Warning: a final empty element has been omitted the part of the args list of 'c' being evaluated was:

Hi, The man page for base::unique.matrix() and base::unique.array() says that MARGIN is expected to be a single integer. OTOH the code in charge of checking the user supplied MARGIN is: if (length(MARGIN) > ndim || any(MARGIN > ndim)) stop(gettextf("MARGIN = %d is invalid for dim = %d", MARGIN, dx), domain = NA) which doesn't really make sense. As

Dear All, There is one problem I encountered when I used ADAPT to compute some 2-D integral w.r.t beta density. For example, when I try to run the following comments: fun2<-function(theta){return(dbeta(theta[1],0.005,0.005)*dbeta(theta[2],0.005,0.005))} int.fun2<-adapt(ndim=2,lo = c(0,0), up = c(1,1),functn = fun2,eps = 1e-4) It seems it will take very long time to run. Acturally, I

...cdf(nc=tg.ncdf,varid="latitude") # ditto timearr = get.var.ncdf(nc=tg.ncdf,varid="time") # reads entire time array targettime = julian(x=1, d=1, y=2002, origin=c(month = 1, day = 1, year = 1950)) inds = (1:dim(timearr)) tind = inds[targettime == timearr] ndims = tg.ncdf$var[['data']]$ndims varsize = tg.ncdf$var[['data']]$varsize start = c( 1, 1, tind) count = c(varsize[1], varsize[2], 1) # Read in data slice: tg.data = get.var.ncdf(nc=tg.ncdf,varid="data",start,count) tg.data[tg.data == -9999] = NA t...

Hi, Suppose I have a multidimensional array: tmp <- array(1:8, c(2,2,2)) is there a function out there that, given a one-dimensional array index, will return the separate indices for each array dimension? for instance, tmp[8] is equivalent to tmp[2,2,2]. I'd like to derive the vector (2,2,2) from the index 8. thanks, Brad Buchsbaum

I would like to do some operations inside a function using only one value for the last dimension of a table/matrix: tabfn <- function (dfrm, facvec, YN ="event"){ return( Etbl <- do.call(table, dfrm[ , c(facvec, "event") ]) ) # just want Etbl[,,,"TRUE"] or Etbl[,, "TRUE"] or Etbl[,"TRUE"] }

Dear R users and experts, I am using Homals to perform categorical PCA on some survey data. The documentation is a bit obscure, however, I followed the examples. X is a matrix with ordinal 1-5 Likert scale entries on 24 questions from about 2500 respondents. So I run X.nlpc = homals(X, rank = 1, level = "ordinal", ndim = 10) to get the first 10 pc's (the number of dimensions is

Dear R-devel, May I suggest that a new feature be added to a couple of unique() methods? Sometimes it's useful to have the indices of the original data that the unique elements come from, so that the original data can be recreated from the unique()ed data. I suggest that an `index' argument be added for unique. Below is a suggested patch against R/src/library/base/R/duplicated.R: ***