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...!nn"); return R_NilValue; } Now in the terminal i type R CMD SHLIB prova2.cpp to create the file prova2.so and this happen without error. In R i type dyn.load("prova2.so") and get this error: Errore in dyn.load("prova2.so") : unable to load shared object '/Users/niandra/Desktop/statistico/r/builtpack/ProvaScript/prova2.so': dlopen(/Users/niandra/Desktop/statistico/r/builtpack/ProvaScript/prova2.so, 6): Symbol not found: __ZN2cv11_InputArrayC1ERKNS_3MatE Referenced from: /Users/niandra/Desktop/statistico/r/builtpack/ProvaScript/prova2.so Expected in: flat...

i'm using the following c++ code using namespace std; #include <iostream> #include <stdio.h> #include <opencv/cv.h> #include <opencv2/core/core.hpp> #include <opencv2/highgui/highgui.hpp> #include <opencv/highgui.h> #include <opencv/cv.h> #include <R.h> #include <Rinternals.h> #include <Rmath.h> extern "C" { SEXP

? stato filtrato un testo allegato il cui set di caratteri non era indicato... Nome: non disponibile URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20120807/70d20fd4/attachment.pl>

Hi all, I have a problem with the library R2BayesX, when i try to use the command bayesx i get this error: dyld: Library not loaded: /usr/local/lib/libreadline.5.2.dylib Referenced from: /Library/Frameworks/R.framework/Versions/2.15/Resources/library/BayesXsrc/libs/i386/BayesX Reason: image not found I obtain this message also with the example in the bayesx help: ## generate some data

Hi, I have a R program that call a C function. I define a vector of pointer as int nLC=3; int pownLC = nLC*nLC double *MatCovExtra[nT+1]; for(k=0;k<K+1;k++) { MatCovExtra[k] = (double*)R_alloc(pownLC, sizeof(double)); } where nT>K. Then i put some values on the vector associated with the pointer: for(k=0;k<K+1;k++) { for(i=0;i<nLC;i++)

Hi all I'm using the function bayesx to estimate a simple model, for example: library(R2BayesX) ## generate some data set.seed(111) n <- 200 ## regressor dat <- data.frame(x = runif(n, -3, 3)) ## response dat$y <- with(dat, 1.5 + sin(x) + rnorm(n, sd = 0.6)) ## estimate models with ## bayesx REML and MCMC b1 <- bayesx(y ~ sx(x), method = "REML", data = dat) I want