similar to: Mode of MCMC chain

Hello, I wonder if someone could send me suggestions on how to solve the following problem: I have a vector of an arbitrary size (ex. data<-c(10,10,11,10,12,11,10,12,11,11,10,11)) and use the table function, which gives the following result 10 11 12 5 5 2 that''s fine, but what I would like to do now is: construct new classes based on the number of classes from table, 10

Hello, I wonder if someone could help me with the following: I have generated 10 000 values from rnorm and now I want to randomly replace 500 of those with NA. The problem is that values indexed between 6-10,16-20,26-30.... only should be considered for replacement. Any suggestions? Patrik Waldmann -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing

Hello, I have an unbalanced data set with some factors and several variables. The missing values are spread unequally over the variables. Because of the unbalanced structure have i tried NLME, but I cannot understand how I should set up the na.omit. I would not like to use na.omit before setting up the model, as that would exclude too many observations (on the whole structure). Lets say I have

Hello again, I was too quick before. What I was looking for was a function that constructs the design (or incidence) matrix (X in a linear model) from a factor. Uwe Ligges suggested using model.matrix and this does almost what I want, but it is first necessary to construct a data variable. It also asigns ones to all rows of the first column (because this is set to be the contrast, not really what

I wonder if someone could help me adjusting the following code to parallelized snow code: #Creating a data set (not needed to be parallel) n<-100 p<-100 x<-matrix(rnorm(n*p),p) y<-rnorm(n) # Bootstrapping nboot<-1000 alpha<-0.05 rhoboot <- array(0, dim=c(p,nboot)) bootranks <- array(0, dim=c(p,nboot)) bootsamples <- array( floor(runif(n*nboot)*n+1), dim=c(n,nboot)) for

Hello, are there any good methods in R that will test if two correlation matrices (obtained in different ways) are equal? Something better than the Mantel test would be preferable. Regards, Patrik Waldmann -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info",

I haven't found a function that directly calculates the matrix inverse, does it exist? Otherwise what would be the fastest way to do it? Patrik Waldmann -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the

Good day Sir/Ma'am! This is Alyssa Fatmah S. Mastura taking up Master of Science in Statistics at Mindanao State University-Iligan Institute Technology (MSU-IIT), Philippines. I am currently working on my master's thesis titled "Comparing the Three Estimation Methods for the Four Parametric Logistic (4PL) Item Response Model". While I am looking for a package about Markov chain

I know of no existing functions for estimating the parameters of this model using MCMC or MML. Many years ago, I wrote code to estimate this model using marginal maximum likelihood. I wrote this based on the using nlminb and gauss-hermite quadrature points from statmod. I could not find that code to share with you, but I do have code for estimating the 3PL in this way and you could modify the

I have an mcmc object and I''m trying to plot the quantiles of the variables - and not as a function of the iterations as in cumuplot. I cannot seem to find the right combination of indexing to access the variables; after which I''m sure I can plot all the statistics I could hope for. Any hints for accessing the mcmc object would be appreciated. =Dave [[alternative HTML

Dear List members, I am using R to generate MCMC time series plots. This is the code I use; however, everytime an error message will come out saying could not find function "plot.mcmc." I have coda package and Lattice package installed. Does anyone know what may get wrong here? Thanks so much for your suggestions. Hongli Li *library (coda) dat1=read.csv("Itemtime.csv")

I have been running a Gibbs Sampler to estimate levels of efficiency in the Louisiana Shrimp Industry. I created a matrix (samp) where I stored the results of each iteration for 86 variables. I run 10,000 iterations. So, the matrix samp is 10,000 x 86. I want to use the gelman-rubin test to check for convergence. To do that, I need at least two chains. If I run second chain with different starting

Hello, I am about to move all of my modelling work into R, and I have been investigating the present state of MCMC and Bayesian methods in R. Following a thread on the mailing list in 2000, I have looked at mcmcpack and Hydra. Three years down the line, is there anything new in this area? I have used both MCSim and WinBUGS in the past. The first one seems promising, but is too focused towards

Hello, I tryed to use the MCMC pack, particularly the function MCMCirtKd to simulate the posterior distribution in a multidimensional IRT model. The code I used is: posterior1 <- MCMCirtKd(Y, dimensions=2, item.constraints=list("V2"=list(3,0)), burnin = 1000, mcmc = 10000, thin=1, verbose = 1, seed = NA, alphabeta.start = NA, b0 = 0, B0=0, store.item = FALSE,

Dear all I am now running a MCMC iteration in the R program. But it is always stucked in some loop. This cause big problems for my research. So I want to know whether we can skip the current dataset and move to next simulated data when the iteration is stucked? Alternatively, can the MCMC chain skip the current iteration when it is stucked and automatically to start another chain with different

Dear list users, I need to learn about MCMC methods, and since there are several packages in R that deal with this subject, I want to use them. I want to buy a book (or more than one, if necessary) that satisfies the following requirements: - it teaches well MCMC methods; - it is easy to implement numerically the ideas of the book, and notation and concepts are similar to the corresponding R

I am receiving the above error ( full r session output below) the script runs OK in windows. and "genotypes" and "ploidy" are both correct arguments any suggestions would be most welcome Nevil Amos MERG/ACB Monash University School of Biological Sciences > library(Geneland) Loading required package: RandomFields Loading required package: fields Loading required

Dear R users, I am leaning MCMC sampling, and have a problem while trying to sample exponential r.v.'s via the following code: samp <- MCMCmetrop1R(dexp, theta.init=1, rate=2, mcmc=5000, burnin=500, thin=10, verbose=500, logfun=FALSE) I tried other distribtions such as Normal, Gamma with shape>1, it works perfectly fine. Can someon

Hi Does anyone know of any R coding/functions for MCMC approaches? I am currently using BUGS but I wonder if the bazaar has produced anything? I think I am pushing BUGS to it's limit and possibly past it at the moment. John -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send

I am trying to get summary statistics from WinBUGS/JAGS output in the form of mcmc.list objects, using the summary() function. However, I get odd warning messages: Warning messages: 1: In glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, : algorithm did not converge 2: In glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, : algorithm did