DirichletProcessMvnormal {dirichletprocess} | R Documentation |
Create a Dirichlet mixture of multivariate normal distributions.
Description
G_0 (\boldsymbol{\mu} , \Lambda | \boldsymbol{\mu _0} , \kappa _0, \nu _0, T_0) = N ( \boldsymbol{\mu} | \boldsymbol{\mu _0} , (\kappa _0 \Lambda )^{-1} ) \mathrm{Wi} _{\nu _0} (\Lambda | T_0)
Usage
DirichletProcessMvnormal(
y,
g0Priors,
alphaPriors = c(2, 4),
numInitialClusters = 1
)
Arguments
y |
Data |
g0Priors |
Prior parameters for the base distribution. |
alphaPriors |
Alpha prior parameters. See |
numInitialClusters |
Number of clusters to initialise with. |
[Package dirichletprocess version 0.4.2 Index]