View source: R/Auxiliary_and_graphics_functions.R
compute_chains_info | R Documentation |
Compute summaries of Gibbs Sampler chains.
compute_chains_info(chain, param)
chain |
a list given by the |
param |
a list containing:
|
Return a list containing the estimates of mu
and sigma_sq
, the
Smooth estimate and the chain autocorrelation for mu
, sigma_sq
and beta
.
param_sim <- list(Q=1, n=100, p=c(50), grids_lim=list(c(0,1))) data <- sim(param_sim,verbose=TRUE) param <- list(iter=5e2, K=c(3), n_chains = 3) res_bliss <- fit_Bliss(data,param,verbose=TRUE,compute_density=FALSE,sann=FALSE) param$grids <- data$grids chains_info1 <- compute_chains_info(res_bliss$chains[[1]],param) chains_info2 <- compute_chains_info(res_bliss$chains[[2]],param) chains_info3 <- compute_chains_info(res_bliss$chains[[3]],param) # Smooth estimates ylim <- range(range(chains_info1$estimates$Smooth_estimate), range(chains_info2$estimates$Smooth_estimate), range(chains_info3$estimates$Smooth_estimate)) plot(data$grids[[1]],chains_info1$estimates$Smooth_estimate,type="l",ylim=ylim, xlab="grid",ylab="") lines(data$grids[[1]],chains_info2$estimates$Smooth_estimate,col=2) lines(data$grids[[1]],chains_info3$estimates$Smooth_estimate,col=3) # Autocorrelation plot(chains_info1$autocorr_lag[,1],type="h")
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