DirichletProcessHierarchicalBeta: Create a Hierarchical Dirichlet Mixture of Beta Distributions

Description Usage Arguments Value

View source: R/dirichlet_process_hierarchical_beta.R

Description

Create a Hierarchical Dirichlet Mixture of Beta Distributions

Usage

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DirichletProcessHierarchicalBeta(dataList, maxY, priorParameters = c(2,
  8), hyperPriorParameters = c(1, 0.125), gammaPriors = c(2, 4),
  alphaPriors = c(2, 4), mhStepSize = c(0.1, 0.1), numSticks = 50,
  mhDraws = 250)

Arguments

dataList

List of data for each separate Dirichlet mixture object

maxY

Maximum value for the Beta distribution.

priorParameters

Prior Parameters for the top level base distribution.

hyperPriorParameters

Hyper prior parameters for the top level base distribution.

gammaPriors

Prior parameters for the top level concentration parameter.

alphaPriors

Prior parameters for the individual parameters.

mhStepSize

Metropolis Hastings jump size.

numSticks

Truncation level for the Stick Breaking formulation.

mhDraws

Number of Metropolis-Hastings samples to perform for each cluster update.

Value

dpobjlist A Hierarchical Dirichlet Process object that can be fitted, plotted etc.


dirichletprocess documentation built on July 2, 2020, 2 a.m.