similar to: R2BayesX help

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 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 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,

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, I'm using R to do a series of calculation and I have gotten several warnings that say "NaNS produced". Whatever I could read on line gives me an idea that this warning is produced when the number is use is a negative log or otherwise mathematically problematic. I'm getting this error while using factorial() and gamma () on strictly positive numbers (always greater than zero).

Hi all, I have a problem with getting my code to do what I want! This is the code I have: create.means.one.size<-function(nsample,var,nboot){ mat.x<-matrix(0,nrow=nboot,ncol=nsample) for(i in 1:nboot){ mat.x[i,]<-sample(var,nsample,replace=T) } mean.mat<-rep(0,nboot) for(i in 1:nboot){ mean.mat[i]<-mean(mat.x[i,]) } sd.mean<-sd(mean.mat) return(mean.mat) } where

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 there, I have a the following function which takes a name(fname), total number of rows (Total), number of times to make a sample(nSample), number of records/rows to be included in each sample(nPatient). then it generates required samples and calculates the mean and standard deviation of the columns for each sample and finally in calculates the grand mean and standard deviation. The problem

Dear R developers and users: I have the following data, x is the response vaiable, nsample(individual) nested within trt, and subsample nested within nsample, I want to fit trt as fixed effect, and block, nsample(trt) as random effects using lme, is the following coding correct? dat$vgrp <- getGroups(dat, form = ~ 1|trt/nsample, level = 2) ge.lme1 <- lme(fixed=x~trt, data=dat,

Can anybody explain why RMA has to have a default normalization method: quantile-quantile? Why don't leave the choices to users? If I just want to use RMA to do a background correction without normalization, how should I specify the ? in the normalize.method="?" ? Hairong [[alternative HTML version deleted]]

I am trying to implement a simple r-svm example using the iris data (only two of the classes are taken and data is within the code). I am running into some errors. I am not an expert on svm's. If any one has used it, I would appreciate their help. I am appending the code below. Thanks../Murli ####################################################### ### R-code for R-SVM ### use leave-one-out

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

Hi everyone, I have a question about functions. I have two functions: Sampling=function(fname,Total,nSample,nPatient){......return(list(Gmean,Gsd))} Power=function(alfa,m1,m2,s1,s2,n1,n2){....return(powe)} I want to use "Gmean" and "Gsd" which are the returned values from "Sampling" function, in "Power" function. i.e. when I call "power" I want

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

Dear list, For educational purposes I have been working with the script below. I have a observation: line 31 #CScal[i] = (amo^2) # IT IS WRONG, I KNOW, BUT IT MAKE R TO CRASHES! I'm thinking this is a possible bug in the R! And I have a couple of doubts: 1) line 51 #curve(dchisq(x, n-1), add = T, col = 'red' I think that it is correct, but the function no

Howdy everyone I?m trying to get Odds ratio and OR confidence intervals using a probit model, but I'm not getting. Do you think you can help me? I?m new with R L naive = summary(glm(pcr.data[,7]~boldBeta_individual+pcr.data$age,family=binomial(link=probit))) naive_answer = c(naive$coefficients[,1:3]) #naive estimates for

Please don't post in HTML. Your post is almost unreadable Also,lease have a look at http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example and/or http://adv-r.had.co.nz/Reproducibility.html for some suggestions about what you should include in your question. Welcome to R. John Kane Kingston ON Canada > -----Original Message----- > From: rosita21 at

Hi, R guys: I'm using L-BFGS-B method of optim for minimization problem. My function called besselI function which need non-negative parameter and the besselI will overflow if the parameter is too large. So I set the constraint box which is reasonable for my problem. But the point outside the box was test, and I got error. My program and the error follows. This program depends on CircStats

I want to get some "simple" logic regression examples to work before exploring a hard problem. I can get results, but I'm having some problems using "cat" to save the logic regression equation to a disk file. Consider this: # Simple Logic Regression Example # efg, 23 Feb 2005 library(LogicReg) # Create simulated data with known logic equation: # "noise"

Hi Caitlin and Ben, Thanks for your responses! My issue is that I'd like to create one continuous line, rather than 3 lines overlayed. The code I've attached works for a population of 400 and samples 100 times. I'd like to extend this to 300 samples and 3 populations. So, the x-axis would range from 0-300 samples. What I'm having trouble with is finding a way to change the