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
)
dpobjlist A Hierarchical Dirichlet Process object that can be fitted, plotted etc.
List of data for each separate Dirichlet mixture object
Maximum value for the Beta distribution.
Prior Parameters for the top level base distribution.
Hyper prior parameters for the top level base distribution.
Prior parameters for the top level concentration parameter.
Prior parameters for the individual parameters.
Metropolis Hastings jump size.
Truncation level for the Stick Breaking formulation.
Number of Metropolis-Hastings samples to perform for each cluster update.