DirichletProcessHierarchicalBeta function

Create a Hierarchical Dirichlet Mixture of Beta Distributions

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.

Returns

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