generatePriorThetaY: PriorThetaY list

In bpgmm: Bayesian Model Selection Approach for Parsimonious Gaussian Mixture Models

PriorThetaY list

Description

generate prior value for parameter Theta and Y.

Usage

generatePriorThetaY(m, n, p, muBar, hparam, qVec, ZOneDim, constraint)

Arguments

m	the number of cluster
n	sample size
p	number of covariates
muBar	parameter
hparam	hyperparameters
qVec	the vector of the number of factors in each clusters
ZOneDim	ZOneDim
constraint	constraint

Examples

m <- 20
n <- 500
p <- 10
muBar <- c(
  -33.1342706763595, -35.2699639183419, 48.276928009445, 16.2370659601218,
  19.0023163870536, -23.4900965314972, 37.1081269873873, 4.74944562930846,
  4.6918997353449, -4.55088073255655
)
hparam <- new("Hparam",
  alpha1 = 0.567755037123148, alpha2 = 1.1870201935945,
  delta = 2, ggamma = 2, bbeta = 3.39466184520673
)
qVec <- c(4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4)
ZOneDim <- sample(seq_len(m), n, replace = TRUE)
constraint <- c(0, 0, 0)
#'

generatePriorThetaY(m, n, p, muBar, hparam, qVec, ZOneDim, constraint)

bpgmm documentation built on June 2, 2022, 1:10 a.m.