Nothing
#' Estimate Dynamic Comparative Public Opinion
#'
#' \code{dcpo} uses diverse survey data to estimate public opinion across countries and over time.
#'
#' @param dcpo_input a data frame of survey items and marginals generated by \code{DCPOtools::dcpo_setup}
#' @param chime play chime when complete?
#' @param ... arguments to be passed to \code{rstan::stan}. Defaults reset by \code{dcpo} are
#' described below under details.
#
#' @details \code{dcpo}, when passed a data frame \code{dcpo_input} of survey marginals created
#' by \code{dcpo_setup}, estimates a latent variable of public opinion. See \code{rstan::stan} for
#' additional options; \code{stan} defaults reset by \code{dcpo} are \code{seed = 324, thin = 2,}
#' \code{cores = min(stan_args$chains, parallel::detectCores()/2),} and \code{control <- list(adapt_delta = 0.99, stepsize = 0.005, max_treedepth = 14)}
#' @examples
#' \donttest{
#' out1 <- dcpo(demsup_data,
#' chains = 1,
#' iter = 300) # 1 chain/300 iterations for example purposes only; use defaults
#' }
#'
#' @return a stanfit object
#'
#' @import rstan
#' @importFrom beepr beep
#'
#' @export
dcpo <- function(dcpo_input,
chime = TRUE,
...) {
dcpo_model <- stanmodels$dcpo
stan_args <- list(object = dcpo_model,
data = dcpo_input,
...)
if (!length(stan_args$control)) {
stan_args$control <- list(adapt_delta = 0.99, stepsize = 0.005, max_treedepth = 14)
}
if (!length(stan_args$seed)) {
stan_args$seed <- 324
}
if (!length(stan_args$thin)) {
stan_args$thin <- 2
}
if (!length(stan_args$cores)) {
stan_args$cores <- min(stan_args$chains, parallel::detectCores()/2)
}
out1 <- do.call(rstan::sampling, stan_args)
# Chime
if(chime) {
try(beep())
}
return(out1)
}
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