BinBlocICL_MLBM {bikm1}

BinBlocICL_MLBM function for computation of the ICL criterion in the MLBM

Description

Produce a plot object representing the resumed co-clustered data-sets.

Usage

BinBlocICL_MLBM(a,b,x,y,z1,v1,w1)

Arguments

a

an hyperparameter for priors on the mixing proportions. By default, a=4.

b

an hyperparameter for prior on the Bernoulli parameter. By default, b=1.

x

binary matrix of observations (1rst matrix).

y

binary matrix of observations (2nd matrix).

z1

a numeric vector specifying the class of rows.

v1

a numeric vector specifying the class of columns (1rst matrix).

w1

a numeric vector specifying the class of columns (2nd matrix).

Value

a value of the ICL criterion.

Examples

require(bikm1)
set.seed(42)
n=200
J=120
K=120
g=2
h=2
l=2
theta=list()
theta$pi_g=1/g *matrix(1,g,1)
theta$rho_h=1/h *matrix(1,h,1)
theta$tau_l=1/l *matrix(1,l,1)
theta$alpha_gh=matrix(runif(4),ncol=h)
theta$beta_gl=matrix(runif(4),ncol=l)
data=BinBlocRnd_MLBM(n,J,K,theta)
res=BIKM1_MLBM_Binary(data$x,data$y,2,2,2,4,init_choice='smallVBayes')
BinBlocICL_MLBM(a=4,b=1,data$x,data$y, data$xrow,data$xcolx,data$xcoly)