Nothing
bayesx.reformate <- function(x)
{
if(!is.null(x$fixed.effects) && length(x$fixed.effects) > 0L) {
e <- x$fixed.effects
type <- if(colnames(e)[1] == "pmode") "REML" else "MCMC"
if(type == "REML") {
tvalues <- e[,1L]/e[,4L]
if(!is.null(x$model.fit$N)) {
pvalues <- 2 * pt(-abs(tvalues), df = x$model.fit$N - 1)
e <- cbind(e[,1L], e[,4L], tvalues, pvalues)
if(!is.matrix(e))
e <- matrix(e, nrow = 1L)
colnames(e) <- c("Estimate", "Std. Error", "t value", "Pr(>|t|)")
} else {
e <- cbind(e[,1L], e[,4L], tvalues)
if(!is.matrix(e))
e <- matrix(e, nrow = 1L)
colnames(e) <- c("Estimate", "Std. Error", "t value")
}
}
if(type == "MCMC") {
e <- e[, c(1L, 2L, 3L, 5L, 7L)]
if(!is.matrix(e))
e <- matrix(e, nrow = 1L)
colnames(e) <- c("Mean", "Sd", "2.5%", "50%", "97.5%")
}
eattrn <- names(attributes(x$fixed.effects))
for(i in 1L:length(eattrn))
if(eattrn[i] != "dim" && eattrn[i] != "dimnames")
attr(e, eattrn[i]) <- attr(x$fixed.effects, eattrn[i])
rownames(e) <- rownames(x$fixed.effects)
if(!is.null(attr(e, "sample")))
if(ncol(attr(e, "sample")) == length(rownames(e)))
colnames(attr(e, "sample")) <- rownames(e)
x$fixed.effects <- e
}
if(!is.null(x$effects) && length(x$effects) > 0L) {
for(i in 1L:length(x$effects)) {
if(!is.null(x$effects[[i]])) {
if(is.list(x$effects[[i]])) {
if(length(x$effects[[i]]) > 0L)
for(j in 1L:length(x$effects[[i]]))
x$effects[[i]][[j]] <- chacol(x$effects[[i]][[j]])
} else x$effects[[i]] <- chacol(x$effects[[i]])
}
}
}
if(!is.null(x$smooth.hyp) && length(x$smooth.hyp) > 0L)
x$smooth.hyp <- recol(chacol(x$smooth.hyp))
if(!is.null(x$random.hyp) && length(x$random.hyp) > 0L)
x$random.hyp <- recol(chacol(x$random.hyp))
if(!is.null(x$variance) && length(x$variance) > 0L)
x$variance <- recol(chacol(x$variance))
return(x)
}
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