EvaluateProposalLambda: EvaluateProposalLambda

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

EvaluateProposalLambda

Description

EvaluateProposalLambda

Usage

EvaluateProposalLambda(hparam, thetaYList, CxyList, constraint, newlambda,
  m, qVec, p)

Arguments

hparam	hparam
thetaYList	thetaYList
CxyList	CxyList
constraint	constraint
newlambda	newlambda
m	the number of clusters
qVec	the vector of the number of factors in each clusters
p	the number of features

Examples

set.seed(100)
n <- 10
p <- 2
q <- 1
K <- 2
m <- 1
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 = 0.366618687752634,
    psy = list(structure(
      c(
        4.18375613018654,
        0, 0, 5.46215996830771
      ),
      .Dim = c(2L, 2L)
    )),
    M = list(structure(
      c(
        3.27412045866392,
        -2.40544145363349
      ),
      .Dim = 1:2
    )),
    lambda = list(structure(
      c(
        2.51015961514781,
        -0.0741189919182549
      ),
      .Dim = 2:1
    )),
    Y = list(structure(
      c(
        -0.244239011725104,
        -0.26876172736886,
        0.193431511203083,
        0.41624466812811,
        -0.54581548068437,
        -0.0479517628308146,
        -0.633383997203325,
        0.856855296613208,
        0.792850576988512,
        0.268208848994559
      ),
      .Dim = c(1L, 10L)
    ))
  )
CxyList <-
  list(
    A = list(structure(
      c(0.567755037123148, 0, 0, 1.1870201935945),
      .Dim = c(2L, 2L)
    )),
    nVec = structure(10, .Dim = c(1L, 1L)),
    Cxxk = list(structure(
      c(
        739.129405647622,
        671.040583460732,
        671.040583460732,
        618.754338945564
      ),
      .Dim = c(2L, 2L)
    )),
    Cxyk = list(structure(
      c(-18.5170828875512, -16.5748393456787),
      .Dim = 2:1
    )),
    Cyyk = list(structure(2.4786991560888, .Dim = c(
      1L,
      1L
    ))),
    Cytytk = list(structure(
      c(
        10, 0.787438922114998, 0.787438922114998,
        2.4786991560888
      ),
      .Dim = c(2L, 2L)
    )),
    Cxtytk = list(structure(
      c(
        -57.5402230447872,
        -54.6677145995824,
        -18.5170828875512,
        -16.5748393456787
      ),
      .Dim = c(
        2L,
        2L
      )
    )),
    CxL1k = list(structure(
      c(-59.5168204264758, -54.6093504204781),
      .Dim = 2:1
    )),
    Cxmyk = list(structure(
      c(
        -21.0952527723962,
        -14.6807011202188
      ),
      .Dim = 2:1
    )),
    sumCxmyk = structure(c(
      -21.0952527723962,
      -14.6807011202188
    ), .Dim = 2:1),
    sumCyyk = structure(3.6657193496833, .Dim = c(
      1L,
      1L
    ))
  )
#'

EvaluateProposalLambda(hparam, thetaYList, CxyList, constraint, thetaYList@lambda, m, qVec, p)

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