#' posterior distribution. The prior distribution is the initial belief of the
#' distribution of R0, which is the uninformative uniform distribution with
#' values between zero and \code{kappa}. Users can change the value of
#' posterior distribution. The prior distribution is the initial belief of the
#' distribution of R0, which is the uninformative uniform distribution with
#' values between zero and \code{kappa}. Users can change the value of
#' uniform). As more case counts are observed, the influence of the prior
#' distribution should lessen on the final estimate \code{Rhat}.
#'
#' uniform). As more case counts are observed, the influence of the prior
#' distribution should lessen on the final estimate \code{Rhat}.
#'
#' \code{Rhat} is the estimate of R0 (the posterior mean),
#' \code{posterior} is the posterior distribution of R0 from which
#' alternate estimates can be obtained (see examples), and \code{group}
#' \code{Rhat} is the estimate of R0 (the posterior mean),
#' \code{posterior} is the posterior distribution of R0 from which
#' alternate estimates can be obtained (see examples), and \code{group}
#' were input and grouping was done to obtain \code{Rhat}). The variable
#' \code{posterior} is returned as a list made up of \code{supp} (the
#' support of the distribution) and \code{pmf} (the probability mass
#' were input and grouping was done to obtain \code{Rhat}). The variable
#' \code{posterior} is returned as a list made up of \code{supp} (the
#' support of the distribution) and \code{pmf} (the probability mass