Any suggestions :( ??From: cute_loo...@hotmail.com To: r-help@r-project.org Subject: Metro_Hastings I wrote my code again Date: Sun, 15 Feb 2015 21:47:25 +0300
Hi again :) I wrote my code here: library("MHadaptive") baysianlog=function (param,data) { alpha=param[1] gam=param[2] delta=param[3] x=data n =length(x) logl=n*log(alpha)+n*log(gam)+n*log(1/delta)+(alpha-1)*sum(log(x))-sum(log(1+(gam)*x^alpha)) p=prior(param) return(logl+p) } prior=function(param) { alpha=param[1] gam=param[2] delta=param[3] prior_alpha=dunif(alpha,min=0, max=1,log=TRUE) prior_gam=dunif(gam,0,1,log=TRUE) prior_delta=dunif(delta,0,1,log=TRUE) return(prior_alpha+ prior_gam +prior_delta) } n=7 ; m=15 alphaB=c();gamB=c();deltaB=c() for( i in 1:m){ alpha=1.8;gam=3;delta=0.8 v= runif(n) x =delta*((1-v)^(-1/gam)-1)^(1/alpha ) mcmc_r=Metro_Hastings(li_func=baysianlog, pars=c(1,1,1),par_names=c('alpha','gamma','delta'),data=x ) alphaB[i] =mean(mcmc_r $ trac[,1]) gamB[i]= mean(mcmc_r $ trac[,2]) deltaB[i]= mean(mcmc_r $ trac[,3]) }#end for ##### The output is: Error in optim(pars, li_func, control = list(fnscale = -1), hessian = TRUE, : non-finite finite-difference value [1] ________________ the problem I think in the : mcmc_r=Metro_Hastings(li_func=baysianlog, pars=c(1,1,1),par_names=c('alpha','gamma','delta'),data=x ) because I did not write the prop_sigma because I don't know how can I calcalute the covariance matrix. somebody told me to compute the cov without itreation then add the reasulting cov matrix to metro hasting using itreation but it also gave me an error Please anybody can check my code and correct it Thank you, Sara [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.