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 1.0.9 Index]