R/dirichlet_process_exponential.R

In dirichletprocess: Build Dirichlet Process Objects for Bayesian Modelling

#'Create a Dirichlet Mixture of Exponentials
#'
#' This is the constructor function to produce a \code{dirichletprocess} object with a Exponential mixture kernel with unknown rate.
#' The base measure is a  Gamma distribution that is conjugate to the posterior distribution.
#'
#' \eqn{G_0(\theta | \alpha _0, \beta_0) =  \mathrm{Gamma} \left(\theta | \alpha_0, \beta_0 \right)}
#'
#'
#'@param y Data
#'@param g0Priors Base Distribution Priors \eqn{\alpha _0 , \beta _0)}
#'@param alphaPriors Alpha prior parameters. See \code{\link{UpdateAlpha}}.
#'@return Dirichlet process object
#'@export
DirichletProcessExponential <- function(y, g0Priors=c(0.01,0.01), alphaPriors=c(2,4)){

  mdObj <- ExponentialMixtureCreate(g0Priors)
  dpObj <- DirichletProcessCreate(y, mdObj, alphaPriors)
  dpObj <- Initialise(dpObj)
  return(dpObj)
}