evaluatePriorLambda {bpgmm}R Documentation

evaluatePriorLambda

Description

evaluate prior value for parameter Lambda

Usage

evaluatePriorLambda(p, m, alpha2, qVec, psy, lambda, constraint, clusInd)

Arguments

p

the number of features

m

the number of clusters

alpha2

hyper parameter

qVec

the vector of the number of factors in each clusters

psy

parameter

lambda

parameter

constraint

the pgmm constraint, a vector of length three with binary entry. For example, c(1,1,1) means the fully constraint model

clusInd

cluster indicator vector

Examples

p <- 10
m <- 20
alpha2 <- 1.18
qVec <- rep(4, m)
delta <- 2
bbeta <- 2
constraint <- c(0, 0, 0)
psy <- generatePriorPsi(
  p,
  m,
  delta,
  bbeta,
  constraint
)
lambda <- generatePriorLambda(
  p,
  m,
  alpha2,
  qVec,
  psy,
  constraint
)
clusInd <- rep(1, m)
#'

evaluatePriorLambda(
  p,
  m,
  alpha2,
  qVec,
  psy,
  lambda,
  constraint,
  clusInd
)


[Package bpgmm version 1.0.7 Index]