similar to: R2BayesX (command bayesx) doesn't work

Hi all, I have a set of 54 files that I need to convert from ASCII grid format to .shp files to .bnd files for BayesX. I have the following R code to operate on those files: library(maptools) library(Grid2Polygons) library(BayesX) library(BayesXsrc) library(R2BayesX) readfunct <- function(x) { u <- readAsciiGrid(x) } modfilesmore <- paste0("MaxFloodDepth_", 1:54,

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

Hi, I wonder if anyone can help me with this issue. I am using R2BayesX. It seems that the model can maximally contain 20 interactions. When the number of interaction terms exceed 20, the code stops working. Here is a piece of toy code. rm(list=ls()) library(BayesX) library(R2BayesX) #data generating model f2<-function(x1,x2,x3,x4) { y<-2*sin(pi*x1)*1.5+exp(2*x2)/3+2 * sin(4 * pi * (x3

Dear All, I have two questions regarding the use of the R2BayesX package for Bayesian analysis. First, is it possible to generate predictions based on the fitted model? According to Gelman and Hill (2007, pp. 361-363), there are at least two ways to do this in BUGS: (1) generate additional data points with the dependent variable coded as missing (and all the independent variables fixed at

Hi all i'm trying to use the opencv's function into R. i wrote a simple script, just for try to understand how use c++ in R, it loads an image and write it with a different name (i know it ), and then write "Hello, World". The file is names prova2.cpp (is the first time i try to use c++ ) #include <stdio.h> #include <opencv/cv.h> #include

Dear Mr. Simon Wood, dear list members, I am trying to fit a similar model with gam from mgcv compared to what I did with BayesX, and have discovered the relatively new possibility of incorporating user-defined matrices for quadratic penalties on parametric terms using the "paraPen" argument. This was really a very good idea! However, I would like to constraint the coefficients

If you mean this paper by Fahrmeir: http://biomet.oxfordjournals.org/cgi/content/abstract/81/2/317 I would recommend BayesX: http://www.stat.uni-muenchen.de/~bayesx/. BayesX interfaces with R and estimates discrete (and continuous) time survival data with penalized regression methods. If you are looking for a bona fide Bayesian survival analysis method and do not wish to spend a lot of time

Hi, I am using GAMs (package mgcv) to smooth event rates in a penalized regression setting and I was wondering if/how one can select the order of the derivative penalty. For my particular problem the order of the penalty (parameter "m" inside the "s" terms of the formula argument) appears to have a larger effect on the AIC/deviance of the estimated model than the

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

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I only recently discovered options("available_packages_filters" = list(add = TRUE, "license/FOSS")) [cf. help("available.packages", package="utils") in R 2.10.0 or later] which goes nicely with my options("checkPackageLicense" = TRUE) [new in R 2.11]. But now I want to purge my library of packages I would not have installed had I known about

Hi I am trying to install "rms" package but while installing it shows following error package 'survival' 2.36-2 is loaded, but >= 2.36.3 is required by 'rms' what to do? i am using linux OS I have tried by updated r-base-core but it didnt work regards GRR [[alternative HTML version deleted]]

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++)

CRAN (and crantastic) updates this week New packages ------------ * Bergm (1.0) Alberto Caimo http://crantastic.org/packages/Bergm Functions implementing Bayesian estimation for exponential random graph models via exchange algorithm Updated packages ---------------- lmtest (0.9-26), logcondens (1.3.5), MTSKNN (0.0-4), pmml (1.2.21), r2lUniv (0.9.4), rattle (2.5.11), rgdal (0.6-23),

Hi Everybody, please can you help me how to call BayesX in R in order to see the graph already exist in BayesX Thanks ---------- Forwarded message ---------- From: <r-help-request@r-project.org> Date: Sat, Jan 22, 2011 at 5:00 AM Subject: R-help Digest, Vol 95, Issue 22 To: r-help@r-project.org Send R-help mailing list submissions to r-help@r-project.org To subscribe or

Hello Everyone,   Learning about R and its wonderful array of functions. If it's not obvious, I usually try to find out what a function stands for. I think this helps me remember better.   One function that has me stumped is "sink." Can anyone tell me if this stands for something?   Thanks,   Paul         __________________________________________________ [[alternative HTML