sugscompPmlcpp: A C++ accelerated version of sugscompPml

In ococrook/sugsvarsel: SUGS algorithm of Wang and Dunson (2011), SUGS VarSel algorithm Crook et al.

Description

A C++ accelerated version of sugscompPml

Usage

sugscompPmlcpp(X, K, N, D, n, phi, betaHat, m, nu, lambda, S, mu_0, nu_0,
  lambda_0, S_0)

Arguments

X	The data matrix with rows as observations
K	An integer specifiying the number of clusters
N	The total number of people to be clustered
D	An integer specifiying the number of variables
n	A numeric vector contain the number of people already allocated to each cluster
phi	A numeric matrix containing the weights for the dirichlet hyperpiors
betaHat	A numeric vector containing the grid of hyperpriors for the dirichlet concentration parameter
m	A numeric matrix containing the means for each component
nu	A numeric vector containg the degrees of freedom for each component
lambda	A numeric vector containing the mean variance hyperparamter for each component
S	A numeric matrix containing the scale prior for each component
mu_0	The mean hyperparameter, default is the column means of the data matrix.
nu_0	The degrees of freedom hyperparameter, the default value is 2 * (D + 2), where D is the number of variables.
lambda_0	The variance of the Guassian mean prior, the dafault value is 0.01.
S_0	The scale hyperparamter, the default value is a tenth of the column variance of the data matrix.

Value

The log PML.

ococrook/sugsvarsel documentation built on May 27, 2019, 12:12 p.m.