DirichletProcessExponential: Create a Dirichlet Mixture of Exponentials

In dirichletprocess: Build Dirichlet Process Objects for Bayesian Modelling

Create a Dirichlet Mixture of Exponentials

Description

This is the constructor function to produce a dirichletprocess object with a Exponential mixture kernel with unknown rate. The base measure is a Gamma distribution that is conjugate to the posterior distribution.

Usage

DirichletProcessExponential(y, g0Priors = c(0.01, 0.01), alphaPriors = c(2, 4))

Arguments

y	Data
g0Priors	Base Distribution Priors \alpha _0 , \beta _0)
alphaPriors	Alpha prior parameters. See UpdateAlpha.

Details

G_0(\theta | \alpha _0, \beta_0) = \mathrm{Gamma} \left(\theta | \alpha_0, \beta_0 \right)

Value

Dirichlet process object

dirichletprocess documentation built on Aug. 25, 2023, 5:19 p.m.