% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/model_parameters.bayesian.R
\name{model_parameters.stanreg}
\alias{model_parameters.stanreg}
\alias{model_parameters.brmsfit}
\title{Parameters from Bayesian Models}
\usage{
\method{model_parameters}{stanreg}(
  model,
  centrality = "median",
  dispersion = FALSE,
  ci = 0.89,
  ci_method = "hdi",
  test = c("pd", "rope"),
  rope_range = "default",
  rope_ci = 1,
  bf_prior = NULL,
  diagnostic = c("ESS", "Rhat"),
  priors = TRUE,
  iterations = 1000,
  effects = "fixed",
  ...
)

\method{model_parameters}{brmsfit}(
  model,
  centrality = "median",
  dispersion = FALSE,
  ci = 0.89,
  ci_method = "hdi",
  test = c("pd", "rope"),
  rope_range = "default",
  rope_ci = 1,
  bf_prior = NULL,
  diagnostic = c("ESS", "Rhat"),
  priors = TRUE,
  iterations = 1000,
  effects = "fixed",
  component = "all",
  ...
)
}
\arguments{
\item{model}{Bayesian model.}

\item{centrality}{The point-estimates (centrality indices) to compute.  Character (vector) or list with one or more of these options: \code{"median"}, \code{"mean"}, \code{"MAP"} or \code{"all"}.}

\item{dispersion}{Logical, if \code{TRUE}, computes indices of dispersion related to the estimate(s) (\code{SD} and \code{MAD} for \code{mean} and \code{median}, respectively).}

\item{ci}{Confidence Interval (CI) level. Default to 0.95 (95\%).}

\item{ci_method}{The type of index used for Credible Interval. Can be
\code{"HDI"} (default, see \code{\link[bayestestR:hdi]{hdi}}), \code{"ETI"}
(see \code{\link[bayestestR:eti]{eti}}) or \code{"SI"}
(see \code{\link[bayestestR:si]{si}}).}

\item{test}{The indices of effect existence to compute. Character (vector) or
list with one or more of these options: \code{"p_direction"} (or \code{"pd"}),
\code{"rope"}, \code{"p_map"}, \code{"equivalence_test"} (or \code{"equitest"}),
\code{"bayesfactor"} (or \code{"bf"}) or \code{"all"} to compute all tests.
For each "test", the corresponding \pkg{bayestestR} function is called
(e.g. \code{\link[bayestestR:rope]{rope}} or \code{\link[bayestestR:p_direction]{p_direction}}) and its results
included in the summary output.}

\item{rope_range}{ROPE's lower and higher bounds. Should be a list of two
values (e.g., \code{c(-0.1, 0.1)}) or \code{"default"}. If \code{"default"},
the bounds are set to \code{x +- 0.1*SD(response)}.}

\item{rope_ci}{The Credible Interval (CI) probability, corresponding to the
proportion of HDI, to use for the percentage in ROPE.}

\item{bf_prior}{Distribution representing a prior for the computation of Bayes factors / SI. Used if the input is a posterior, otherwise (in the case of models) ignored.}

\item{diagnostic}{Diagnostic metrics to compute.  Character (vector) or list with one or more of these options: \code{"ESS"}, \code{"Rhat"}, \code{"MCSE"} or \code{"all"}.}

\item{priors}{Add the prior used for each parameter.}

\item{iterations}{The number of bootstrap replicates. This only apply in the case of bootstrapped frequentist models.}

\item{effects}{Should results for fixed effects, random effects or both be returned?
Only applies to mixed models. May be abbreviated.}

\item{...}{Arguments passed to or from other methods. For instance, when \code{bootstrap = TRUE}, arguments like \code{ci_method} are passed down to \code{\link[bayestestR]{describe_posterior}}.}

\item{component}{Model component for which parameters should be shown. May be one of \code{"conditional"}, \code{"precision"} (\pkg{betareg}), \code{"scale"} (\pkg{ordinal}), \code{"extra"} (\pkg{glmx}) or \code{"all"}.}
}
\value{
A data frame of indices related to the model's parameters.
}
\description{
Parameters of Bayesian models.
}
\examples{
\donttest{
library(parameters)
if (require("rstanarm")) {
  model <- rstanarm::stan_glm(Sepal.Length ~ Petal.Length * Species,
    data = iris, iter = 500, refresh = 0
  )
  model_parameters(model)
}
}
}
\seealso{
\code{\link[parameters:standardize_names]{standardize_names()}} to rename
  columns into a consistent, standardized naming scheme.
}
