% Generated by roxygen2: do not edit by hand % Please edit documentation in R/map_estimate.R \name{map_estimate} \alias{map_estimate} \alias{map_estimate.numeric} \alias{map_estimate.stanreg} \alias{map_estimate.brmsfit} \title{Maximum A Posteriori probability estimate (MAP)} \usage{ map_estimate(x, precision = 2^10, method = "kernel", ...) \method{map_estimate}{numeric}(x, precision = 2^10, method = "kernel", ...) \method{map_estimate}{stanreg}(x, precision = 2^10, method = "kernel", effects = c("fixed", "random", "all"), parameters = NULL, ...) \method{map_estimate}{brmsfit}(x, precision = 2^10, method = "kernel", effects = c("fixed", "random", "all"), component = c("conditional", "zi", "zero_inflated", "all"), parameters = NULL, ...) } \arguments{ \item{x}{Vector representing a posterior distribution. Can also be a \code{stanreg}, \code{brmsfit} or a \code{BayesFactor} model.} \item{precision}{Number of points of density data. See the \code{n} parameter in \link[=density]{density}.} \item{method}{Density estimation method. Can be \code{"kernel"} (default), \code{"logspline"} or \code{"KernSmooth"}.} \item{...}{Currently not used.} \item{effects}{Should results for fixed effects, random effects or both be returned? Only applies to mixed models. May be abbreviated.} \item{parameters}{Regular expression pattern that describes the parameters that should be returned. Meta-parameters (like \code{lp__} or \code{prior_}) are filtered by default, so only parameters that typically appear in the \code{summary()} are returned. Use \code{parameters} to select specific parameters for the output.} \item{component}{Should results for all parameters, parameters for the conditional model or the zero-inflated part of the model be returned? May be abbreviated. Only applies to \pkg{brms}-models.} } \value{ A numeric value if \code{posterior} is a vector. If \code{posterior} is a model-object, returns a data frame with following columns: \itemize{ \item \code{Parameter} The model parameter(s), if \code{x} is a model-object. If \code{x} is a vector, this column is missing. \item \code{MAP_Estimate} The MAP estimate for the posterior or each model parameter. } } \description{ Find the \strong{Highest Maximum A Posteriori probability estimate (MAP)} of a posterior, i.e., the value associated with the highest probability density (the "peak" of the posterior distribution). In other words, it is an estimation of the \emph{mode} for continuous parameters. Note that this function relies on \link{estimate_density}, which by default uses a different smoothing bandwidth (\code{"SJ"}) compared to the legacy default implemented the base R \link{density} function (\code{"nrd0"}). } \examples{ library(bayestestR) posterior <- rnorm(10000) map_estimate(posterior) plot(density(posterior)) abline(v = map_estimate(posterior), col = "red") \dontrun{ library(rstanarm) model <- rstanarm::stan_glm(mpg ~ wt + cyl, data = mtcars) map_estimate(model) library(brms) model <- brms::brm(mpg ~ wt + cyl, data = mtcars) map_estimate(model) } }