% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/bayesRecon_TDcond.R
\name{make_PMF}
\alias{make_PMF}
\title{Create a discrete PMF from distributions}
\usage{
make_PMF(dist, negative_to_zero = FALSE, toll = 1e-09, alpha_smoothing = 1e-09)
}
\arguments{
\item{dist}{A vector or list of \code{distributional} objects.}

\item{negative_to_zero}{Logical, currently unused. Reserved for future use.}

\item{toll}{Tail probability used to truncate the support when estimating the PMF.}

\item{alpha_smoothing}{Numeric, currently unused. Reserved for future use.}
}
\value{
A list of numeric vectors, one PMF per input distribution.
}
\description{
Converts a set of distributional objects into a list of discrete PMFs used by
the top-down conditioning reconciliation. The function enforces nonnegative,
integer support by truncating negative supports and rounding non-integer
supports via sampling, then estimates the PMF up to the (1 - toll)
quantile.
}
\keyword{internal}
