search for: ndim

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 solution is ndim <- length(dim(x)) args <- rep(",", ndim) args[1] <- "i" args <- paste(args, collapse=&quo...

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 some traps in my code to handle them correctly. I apologize for not i...

...tion(i)identical(z[i],zt[pos[i]])))}) rm(x) } duplicated.matrix <- duplicated.array <- function (x, incomparables = FALSE, fromLast = FALSE, MARGIN = 1, hashFUN=list, ...) { if (!is.logical(incomparables) || incomparables) .NotYetUsed("incomparables != FALSE") ndim <- length(dim(x)) if (length(MARGIN) > ndim || any(MARGIN > ndim)) stop("MARGIN = ", MARGIN, " is invalid for dim = ", dim(x)) temp <- apply(x, MARGIN, hashFUN) d <- dim(temp) dn <- dimnames(temp) dim(temp) <- NULL # we had as.v...

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

...uot;,x,phi,n) [[1]] [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 [[2]] [1] 0.75 [[3]] [1] 20 What's wrong? I don't know how to deal with it. Any suggestions would be great appreciated. Thanks in advance. -------FORTRAN CODE: prog.f------- SUBROUTINE ARSIM_(X,NDIM,PHI) INTEGER NDIM REAL X(NDIM),PHI IF(NDIM.GT.1)THEN DO 10 I=2,NDIM X(I) = PHI*X(I-1)+X(I) 10 CONTINUE ENDIF RETURN END ---------------------------- > R.version _ platform i386-pc-mingw32 arch i386 os...

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 "ncomp" is missing, with no default

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 'factor' levels for (i in unique(fac)) print(apply(m[fac==i,],2,mean)) Now, the problem is that if a value in 'fac' only occurs once, the 'apply' fun...

...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...

...hanks in advance for any help I can receive. I am not god with FORTRAN - very very infrequent FORTRAN user. I am using R 2.4.0. Regards Krishna. > rm(list=ls(all=TRUE)) > dyn.load("c:/smooth.dll") > is.loaded("smooth") [1] TRUE > NROW<-4 > NCOL<-4 > NDIM<-4 > NCYCLE<-5 > X<-array(c(0.05,0.2,0.35,0.43,0.09,0.29,0.41,0.55,0.2,0.33,0.55,0.7,0.33,0.48,0.6,0.8)) > W<-array(rep(1.0,length(X))) > X<-matrix(X,nrow=4,ncol=4) > X<-t(X) > W<-matrix(W,nrow=4,ncol=4) > A<-array(0,dim=c(NROW,NCOL,4)) > B<-array(...

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]]

...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: (paste("Ifail=2, lenwrk was too small. -- fix adapt() !\n", "Check the returned relerr!"), "Ifail=3: ndim > 20 -- rewrite the fortran code ;-) !", "Ifail=4, minpts > maxpts; should not happen!", "Ifail=5, internal non-convergence; should not happen!", ) When it finishes: Warning messages: 1: Ifail=2, lenwrk was too small. -- fix adapt() ! Check the returned relerr! in:...

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 a consequence the user gets an obscure error message when specifying a MARGIN that satisfies the above check but is in f...

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 stopped the program after it was running for like 20 minutes. I thought this might be due to the inclusion of the lower and upper in to the integral computation, so I tried to change the...

...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...

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"] }

...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 irrelevant to my problem). I happen to get eigenvalues in nondecreasing order and I am not sure how to interpret this. Can someone help me? By the way, I would also be interested in knowing if someone has ever compared the homals so...

...62 ---- } unique.matrix <- unique.array <- ! function(x, incomparables = FALSE , MARGIN = 1, index=FALSE, ...) { if(!is.logical(incomparables) || incomparables) .NotYetUsed("incomparables != FALSE") *************** *** 66,70 **** args <- rep(alist(a=), ndim) names(args) <- NULL args[[MARGIN]] <- !duplicated(as.vector(temp)) ! do.call("[", c(list(x=x), args, list(drop=FALSE))) } --- 67,76 ---- args <- rep(alist(a=), ndim) names(args) <- NULL args[[MARGIN]] <- !duplicated(as.vector(temp)) !...