#' @param prior_aux The prior distribution for the "auxiliary" parameter (if
#' applicable). The "auxiliary" parameter refers to a different parameter
#' depending on the \code{family}. For Gaussian models \code{prior_aux}
#' controls \code{"sigma"}, the error
#' standard deviation. For negative binomial models \code{prior_aux} controls
#' \code{"reciprocal_dispersion"}, which is similar to the
#' \code{"size"} parameter of \code{\link[stats:NegBinomial]{rnbinom}}:
#' smaller values of \code{"reciprocal_dispersion"} correspond to
#' greater dispersion. For gamma models \code{prior_aux} sets the prior on
#' to the \code{"shape"} parameter (see e.g.,
#' \code{\link[stats:GammaDist]{rgamma}}), and for inverse-Gaussian models it is the
#' so-called \code{"lambda"} parameter (which is essentially the reciprocal of
#' a scale parameter). Binomial and Poisson models do not have auxiliary
#' parameters.
#'
#' The default prior is described in the vignette
#' \href{https://mc-stan.org/rstanarm/articles/priors.html}{\emph{Prior
#' Distributions for rstanarm Models}}.
#' If not using the default, \code{prior_aux} can be a call to
#' \code{exponential} to use an exponential distribution, or \code{normal},
#' \code{student_t} or \code{cauchy}, which results in a half-normal, half-t,
#' or half-Cauchy prior. See \code{\link{priors}} for details on these
#' functions. To omit a prior ---i.e., to use a flat (improper) uniform
#' prior--- set \code{prior_aux} to \code{NULL}.
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