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##
## PURPOSE: Computation of the predictive marginal (univariate) densities
## * method for objects of class GLMM_MCMC
##
## AUTHOR: Arnost Komarek (LaTeX: Arno\v{s}t Kom\'arek)
## arnost.komarek[AT]mff.cuni.cz
##
## CREATED: 24/07/2009
##
## FUNCTIONS: NMixPredDensMarg.GLMM_MCMC (24/07/2009)
##
## ======================================================================
## *************************************************************
## NMixPredDensMarg.GLMM_MCMC
## *************************************************************
NMixPredDensMarg.GLMM_MCMC <- function(x, grid, lgrid=500, scaled=FALSE, ...)
{
if (missing(grid)){
grid <- list()
if (scaled){
if (x$dimb == 1){
rangeGrid <- 0 + c(-3.5, 3.5)*1
grid[[1]] <- seq(rangeGrid[1], rangeGrid[2], length=lgrid)
}else{
for (i in 1:x$dimb){
rangeGrid <- 0 + c(-3.5, 3.5)*1
grid[[i]] <- seq(rangeGrid[1], rangeGrid[2], length=lgrid)
}
}
}else{
if (x$dimb == 1){
rangeGrid <- x$summ.b.Mean["Median"] + c(-3.5, 3.5)*x$summ.b.SDCorr["Median"]
grid[[1]] <- seq(rangeGrid[1], rangeGrid[2], length=lgrid)
}else{
for (i in 1:x$dimb){
rangeGrid <- x$summ.b.Mean["Median", i] + c(-3.5, 3.5)*x$summ.b.SDCorr["Median", (i-1)*(2*x$dimb - i + 2)/2 + 1]
grid[[i]] <- seq(rangeGrid[1], rangeGrid[2], length=lgrid)
}
}
}
names(grid) <- paste("b", 1:x$dimb, sep="")
}
if (x$dimb == 1) if (is.numeric(grid)) grid <- list(b1=grid)
if (!is.list(grid)) stop("grid must be a list")
if (scaled) scale <- list(shift=0, scale=1)
else scale <- x$scale.b
if (x$prior.b$priorK == "fixed"){
return(NMixPredDensMarg.default(x=grid, scale=scale, K=x$K_b, w=as.numeric(t(x$w_b)), mu=as.numeric(t(x$mu_b)), Li=as.numeric(t(x$Li_b)), Krandom=FALSE))
}else{
return(NMixPredDensMarg.default(x=grid, scale=scale, K=x$K_b, w=x$w_b, mu=x$mu_b, Li=x$Li_b, Krandom=TRUE))
}
}
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