search for: burnin

Dear All, I have a MCMC result in x1. I was wondering if there is a simpler, more elegant way of evaluating the estimate of an integral then this (I am pretty sure there is): Also if I want to count the x's say -1<x<2 but not the ones in the burn in period. [code] z <- -2 burnin <- 2000 int1 <- length(x1$x[(burnin+1):length(x1$x)][x1$x[(burnin+1):length(x1$x)]<z])/(length(x1$x)-burnin) [\code] Thank you: Daniel

...{ + path.sp<- paste(theWd,sp,"/",sep="") + dir.create(path.sp) + GENO.TABLE<-paste(theWd,sp,"geno",sep="") + XY.TABLE<-paste(theWd,sp,"xy",sep="") + MINPOP=1 + MAXPOP=25 + INITPOP=1 + NITS=500000 + THIN=NITS/1000 + nrun <- 10 + burnin <- 200 + geno<-noquote(read.table(GENO.TABLE)) + coord<-read.table(XY.TABLE) + + ## Loop for multiple runs + + for(irun in 1:nrun) + { + ## define path to MCMC directory + + path.mcmc <- paste(path.sp,irun,"/",sep="") + dir.create(path.mcmc) + MCMC(coordinates=coord,...

Deal all, as MCMClogit does not allow for the specification of several chains, I have run my model 3 times with different random number seeds and differently dispersed multivariate normal priors. For example: res1 = MCMClogit(y~x,b0=0,B0=0.001,data=mydat, burnin=500, mcmc=5500, seed=1234, thin=5) res2 = MCMClogit(y~x,b0=1,B0=0.01,data=mydat, burnin=500, mcmc=5500, seed=5678, thin=5) res3 = MCMClogit(y~x,b0=5,B0=0.0001,data=mydat, burnin=500, mcmc=5500, seed=91011, thin=5) Each result produces an object of class mcmc. In order to use the Gelman-Rubin diagn...

...plot average of y instead of all y values, since one can easily see the trend if there is to many points and/or x might be like 1, 2, 3, 4, 5, ... and you might get a cloud (which can also be informative) and/or columns of points. Anyway, learning with R i get stucked. I have the data in table burnins1, with the following names: names(burnins1) [1] "Model" "Replication" "h2" "burnin" and some data ... ... 380 New 80 2 23 381 New 81 5 38 382 New 82 10 31 383 New 83 15 98 384...

...53,50,49,51,47,53,50,49,55,53,48,54,46), y=c(50,49,57,52,47,52,58,45,55,54,51,54,56,53,52,47,51,54,50,47,46,44,54,55,52,57,52,48,48,51)) dat <- format4Bugs(dat, digits = 0) parm <- c("lbda") bugs(dat, inits=list(NULL), parm, "d2.bug", n.chains = 1, n.iter = 5000, n.burnin = floor(n.iter/2), n.thin = max(1, floor(n.chains * (n.iter - n.burnin)/1000)), bin = (n.iter - n.burnin) / n.thin, debug = TRUE, DIC = TRUE, digits = 5, codaPkg = FALSE, bugs.directory = "C:/WinBUGS14/", working.directory = NULL, clearWD = FALSE) The objective of the program is t...

...its.beta0 <- 0 inits <- function(){list(beta=inits.beta,beta0=inits.beta0,taueps=1.0E-3)} parameters <- list("sigma","beta","beta0","y.star") fitm <- bugs(data,inits,parameters,model.file="model.bug", n.chains=3, n.iter=n.iter, n.burnin=n.burnin, n.thin = n.thin, debug=FALSE,DIC=FALSE,digit=5,codaPkg=FALSE, bugs.directory="C:/Program Files/WinBUGS14/") but I always get the following error: Error in FUN(X[[1L]], ...) : .C(..): 'type' must be "real" for this format I tried the web, but f...

Hi, A question. When I run gelman.diag and gelman.plot with mcmc lists obtained from MCMCregress, the results are following. > post.R <- MCMCregress(Size~Age+Status, data = data, burnin = 5000, mcmc = 100000, + thin = 10, verbose = FALSE, beta.start = NA, sigma2.start = NA, + b0 = 0, B0 = 0, nu = 0.001, delta = 0.001) > post1.R <- MCMCregress(Size~Age+Status, data = data, burnin = 5000, mcmc = 100000, + thin = 10, verbose = FALSE, beta.start = -3, si...

...ackage for Fitting the Multinomial Probit Models Version: 1.3-1 URL: http://www.princeton.edu/~kimai/research/MNP.html > > res1 <- mnp(PREVOTE3 ~ 1, choiceX = list(1=UCLC, 2=UDLC, 3=UPLC), Error: syntax error > cXnames = "ut", data = small, n.draws = 500, burnin = 100, Error: syntax error > verbose = TRUE) Error: syntax error > > # another try giving arbitrary names to the values of the dependent variable > > res1 <- mnp(PREVOTE3 ~ 1, choiceX = list(Clinton=UCLC, Dole=UDLC, Perot=UPLC), + cXnames = &...

...I am somewhat unclear as to why this is so. The code for the method is as follows. Any thoughts would be greatly appreciated, and if this works out, feel free to use it yourself! Could be quite useful! -Jarrett #note, the test run was something along the lines of c.bugs<-coda2bugs (n.burnin=1000) coda2bugs<-function(codafile="jags.out", indexfile="jags.ind", n.chains=1, n.iter=NA, n.burnin=NA, n.thin=1, DIC=FALSE, file.rm=T, ...){ require(R2WinBUGS) #first, split up the coda file for R2WinBUGS codaSplit(codafile, indexfile) #get the param...

...Support provided by the U.S. National Science Foundation ## (Grants SES-0350646 and SES-0350613) ## [1] TRUE Warning message: package 'MASS' was built under R version 2.4.1 > a0 = 0.5 > b0 = 1 > mu0 = 0 > beta.init=list(c(0, rep(0.1,4)), c(0, rep(-0.1,4)), c(0, rep(0, 4))) > burnin.cycles = 1000 > mcmc.cycles = 25000 > # three chains > post.list <- lapply(beta.init, function(vec) + { + posterior <- MCMClogit(y~x1+x2+x3+x4, data=c.df, burnin=burnin.cycles, mcmc=mcmc.cycles, + thin=5, tune=0.5, beta.start=vec, user.prior.density=logpriorfun, logfun=TRUE, + mu=mu0...

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, store.ability=FALSE, drop.constant.items=TRUE) where Y is a matrix subjects x items (1500 x 32) of simulated response sequences. After running the program, if I ask for a plot or...

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 tell me why? Thank you for your help. Best, Zhongyi [[alternative HTML version deleted]]

...segfault *** address 0xb31941cc, cause 'memory not mapped' Traceback: 1: .C("siarmcmcv4", as.integer(numdata), as.integer(numsources), as.integer(numiso), as.integer(numgroups), as.integer(startgroup), as.integer(endgroup), as.integer(siardata$iterations), as.integer(siardata$burnin), as.integer(siardata$howmany), as.integer(siardata$thinby), as.double(prior), as.data.frame(data2), as.data.frame(concdepdata), as.data.frame(sourcedata), as.data.frame(correctionsdata), as.data.frame(parameters)) 2: siarmcmcdirichletv4(target, source, fraction, iterations = 5e+05, burnin = 1e+05...

Hi, I am trying to use WinBUGS using R, but i am having some problems using bugs function: out <- bugs(data = win.data, inits = inits, parameters.to.save = params, model.file = "model.txt", n.thin = nt, n.chains = nc, n.burnin = nb, n.iter = ni, debug = TRUE, DIC = TRUE, working.directory = getwd()) ls() WinBUGS file is in working directory=D:/Line/documents but R looks for winBugs at C:/Program Files/WinBUGS14/. I already had changed the working directory for D:/Line/documents using setwd () function and it still a...

...ning R2WinBugs on a setup that previously worked for me (Dell Laptop, Windows XP service pack 3, R 2.11.1, WinBugs 1.43) . When I issue the following command smds.sim <- bugs (data, inits, parameters, "SMDSbrandLoc2.bug", debug = T, n.thin = n.thin, n.chains = n.chains, n.burnin = n.burnin, n.iter = n.iter) I get the following error in R Error in while (.regexpr("\r", info) > 0) { : argument is of length zero Also in WinBugs I get the following messages dic.set() command #Bugs:dic.set cannot be executed (is greyed out) update(5) coda(*,C:...

...################################### ### code chunk number 3: exchange ################################################### exchange.mod <- "model{ for(i in 1:N){ y[i] ~ dnorm(mu, tau) } mu ~ dnorm(0,.001) tau ~ dgamma(.1,.1) }" exchange.out <- run.jags(exchange.mod, data=dat, burnin=10000, sample=50000, thin=5, monitor=c("mu", "tau"), monitor.deviance=T, monitor.pd=T, silent.jags=T) ################################################### ### code chunk number 4: exchange ################################################### FE.mod <- "model{ for...

Hi, I tried to use MethComp library and this library make use of the WinBUGS by R2WinBuGUS, but I get the follow error in bugs.run: *Error in bugs.run(n.burnin, bugs.directory, WINE = WINE, useWINE = useWINE, : * Look at the log file and try again with 'debug=TRUE' to figure out what went wrong within Bugs. Anyone can help-me, please? Thanks Cleber library( MethComp ) library( R2WinBUGS ) library( Epi ) # source("c:/stat/r/bxc/librar...

...e of the methods appear to be the ones that I want. The methods listed are r0, r1, r2, r2dtable, swap, tswap. However, I want to know how to go about implementing fixed row algorithms, as suggested in Gotelli 2000 in Ecology. Also, the null models created seem to be incredibly dependent on the 1) burnin and 2) thin values. These are the 1) Number of null communities discarded before proper analysis in sequential methods "swap" and "tswap" and 2) Number of discarded null communities between two evaluations of nestedness statistic in sequential methods "swap" and "...

...I(baRatio - 0.985) 2.57 0.45 delta 0.22 -0.12 -0.94 Residual 0.39 number of obs: 494, groups: subject, 13 deviance = 551.4 > e7.sim <- mcsamp(e7.lmer2) Error in as.bugs.array(sims, program = "lmer", n.iter = n.iter, n.burnin = n.burnin, : error in parameter sigma. in parameters.to.save **************************************** I would appreciate a pointer to what the problem might be. _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400 Char...

Hi all, I'm trying to run some monte carlo simulation for my roll call data using the ideal() function, which resides in the pscl package. However, I'm receiving an error message that I don't understand. Error in ideal(a, maxiter = 1000, thin = 10, burnin = 50, store.item = TRUE, : NA/NaN/Inf in foreign function call (arg 13) my code is simple the following: > m_a <- ideal(a, maxiter = 1000, thin = 10, burnin = 50, + store.item = TRUE, normalize=T, + priors=list(xp=1e-12,xpv=1e-12,bp=1e-12,bpv=1e-12), verbose=T) ideal: analys...