runSugs: The SUGS clustering algorithm by Wang and Dunson (2011)

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

Description

The SUGS clustering algorithm by Wang and Dunson (2011)

Usage

runSugs(iter, mydata, Model, mu_0 = NULL, lambda_0 = 0.01, nu_0 = NULL,
  S_0 = NULL, betaHat = c(1, 5, 15, 30, 50, 100), a = 10, b = 1,
  BPPARAM = bpparam())

Arguments

iter	The number of random orderings of the observations for which to run sugs.
mydata	Data matrix with observations as rows
Model	Character string indicating whether to use PML, ML or both for model selection. "Both" defaults to PML.
mu_0	The mean hyperparameter, default is the column means of the data matrix.
lambda_0	The variance of the Guassian mean prior, the dafault value is 0.01.
nu_0	The degrees of freedom hyperparameter, the default value is 2 * (D + 2), where D is the number of variables.
S_0	The scale hyperparamter, the deault value is a tenth of the column variance of the data matrix.
betaHat	A grid of hyperparameters for the dirichlet concentration parameter, the default is c(1, 5, 15, 30, 50, 100).
a	The scale of the gamma prior for the dirichlet concentration parameter, the dafault value is 10.
b	The rate of the gamma prior for the dirichlet concentration parameter, the default value is 1.
BPPARAM	Support for parallel processing using the BiocParallel infrastructure. When missing (default), the default registered BiocParallelParam parameters are used. Alternatively, one can pass a valid BiocParallelParam parameter instance: SnowParam, MulticoreParam, DoparParam, ... see the BiocParallel package for details. To revert to the origianl serial implementation, use serialParam.

Value

A matrix of cluster allocation, K the number of clusters, a matrix indicating the number of observations allocated to each cluster. The value of the model selection criteria either log PML, log ML or both and the random orderings used

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