% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/priors.R
\name{prior_factor}
\alias{prior_factor}
\title{Factor Prior}
\usage{
prior_factor(
  distribution,
  parameters,
  truncation = list(lower = -Inf, upper = Inf),
  prior_weights = 1,
  contrast = "meandif"
)
}
\arguments{
\item{distribution}{character. Prior distribution name.}

\item{parameters}{list. Distribution parameters.}

\item{truncation}{list with \code{lower} and \code{upper} truncation bounds.}

\item{prior_weights}{numeric prior model weight.}

\item{contrast}{character. Contrast coding used for factor levels. Common
RoBMA model options are \code{"treatment"}, \code{"meandif"}, and
\code{"orthonormal"}; the standalone helper also accepts BayesTools contrast
aliases such as \code{"independent"}.}
}
\value{
An object inheriting from \code{prior}, \code{prior.factor}, and a
contrast-specific marker class.
}
\description{
Create priors on factor contrasts.
}
\details{
Mean-difference and orthonormal contrasts require vector or
multivariate priors. Treatment/dummy and independent contrasts use univariate
simple priors per contrast coefficient.
}
