getRemovedIndThetaY: getRemovedIndThetaY

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

getRemovedIndThetaY

Description

getRemovedIndThetaY

Usage

getRemovedIndThetaY(thetaYList, Ind)

Arguments

thetaYList	thetaYList
Ind	Ind

Examples

set.seed(100)
n <- 10
p <- 2
q <- 1
K <- 2
m <- 2
muBar <- c(0, 0)
qVec <- c(1, 1)
constraint <- c(0, 0, 0)
X <- t(
  fabMix::simData(
    sameLambda = TRUE,
    sameSigma = TRUE,
    K.true = K,
    n = n,
    q = q,
    p = p,
    sINV_values = 1 / ((1:p))
  )$data
)
hparam <- new(
  "Hparam",
  alpha1 = 0.567755037123148,
  alpha2 = 1.1870201935945,
  delta = 2,
  ggamma = 2,
  bbeta = 3.39466184520673
)
ZOneDim <- sample(seq_len(m), n, replace = TRUE)
thetaYList <-
  new("ThetaYList", tao = c(0.90162050961987, 0.0983794903801295),
  psy = list(structure(c(3.68472841602225, 0, 0, 8.34691978354054),
  .Dim = c(2L, 2L)), structure(c(0.785011896130842, 0, 0, 1.19022383323437),
  .Dim = c(2L, 2L))), M = list(structure(c(
    2.96424305287004,
    1.08454861414306
  ), .Dim = 1:2), structure(c(
    -0.232625450433964,
    0.984505960868685
  ), .Dim = 1:2)), lambda = list(structure(c(
    -0.964026624054337,
    0.89378616732449
  ), .Dim = 2:1), structure(c(
    0.533334148228635,
    -1.80033696090263
  ), .Dim = 2:1)), Y = list(structure(c(
    -0.15346475266988,
    1.6584112693271, 0.409294936277862, -1.46628591247549, -0.532753243163142,
    -0.332143130316749, 0.307558110800446, -0.525374243612587, 0.527667526535661,
    0.748193650431916
  ), .Dim = c(1L, 10L)), structure(c(
    0.571325118638535,
    0.542462985882966, 0.559971315637159, -1.73905343105432, -0.583549598471542,
    1.71264245945391, -0.327119395945831, 1.02464651767821, -1.11462280255215,
    0.81095592501554
  ), .Dim = c(1L, 10L))))
Ind <- 1
#'

getRemovedIndThetaY(thetaYList, Ind)

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