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#'@title Coefficients for xis
#'@aliases summary_xi
#'@name summary_xi
#'@description A function that uses posterior distribution values of the model and calculates the estimates for xi parametrer.
#'@usage summary_xi(x,prob=0.95)
#'@param x an object of the class \emph{bayesbr}, containing the list returned from the \code{\link{bayesbr}} function.
#'@param prob a probability containing the credibility index for the HPD interval for the coefficients of the covariates.
#'@return A list containing the estimates for xi parametrer, this list contains the following items:
#'\describe{
#'\item{table}{a table with the means, medians, standard deviations and the Highest Posterior Density (HPD) Interval,}
#'\item{coeff}{a vector containing the estimated coefficients.}}
#'@seealso \code{\link{summary_delta}},\code{\link{values}},\code{\link{summary.bayesbr}}
summary_xi = function(x,prob=0.95){
xis = x$info$samples$xi
n = x$info$n
warmup = x$info$warmup
iter = x$info$iter
table = NULL
coeff = numeric()
for (i in 1:n) {
aux = paste0('xi[',i,']')
xi = xis[[aux]]
mean_t = round(mean(xi),5)
coeff = c(coeff,mean_t)
median_t = round(median(xi),5)
sd_t = round(sd(xi),5)
xi_mcmc = as.mcmc( c(xi) )
hpd = HPDinterval(xi_mcmc, prob=prob)
vec = c(mean_t,median_t,sd_t,round(hpd[1:2],5))
table = rbind(table,vec)
}
colnames(table) = c("Mean","Median", "Std. Dev.","HPD_inf","HPD_sup")
rownames(table) = paste0("xi ",1:n)
names(coeff) = paste0("xi ",1:n)
list = list(table = table,xis = coeff)
return(list)
}
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