PoissonBlocICL-proc: PoissonBlocICL function for the computation of the ICL...

In bikm1: Co-Clustering Adjusted Rand Index and Bikm1 Procedure for Contingency and Binary Data-Sets

Description

Produce a value of the ICL criterion for co-clustering partitions

Usage

PoissonBlocICL(a,alpha,beta,x,v1,w1,normalization)

Arguments

a	hyperparameter used in the VBayes algorithm for priors on the mixing proportions. By default, a=4.
alpha	hyperparameter used in the VBayes algorithm for prior on the Poisson parameter. By default, alpha=1.
beta	hyperparameter used in the VBayes algorithm for prior on the Poisson parameter. By default, beta=0.01.
x	contingency matrix of observations.
v1	a numeric vector specifying the class of rows.
w1	a numeric vector specifying the class of columns.
normalization	logical. To use the normalized Poisson modelling in the Latent Block Model. By default normalization=FALSE.

Value

a value of the ICL criterion

Examples

require(bikm1)
J=200
K=120
h=3
l=2
theta=list()
theta$rho_h=(1/h)*matrix(1,h,1)
theta$tau_l=(1/l)*matrix(1,l,1)
theta$gamma_hl=matrix(c(1, 6,4, 1, 7, 1),ncol=2)
data=PoissonBlocRnd(J,K,theta)
res=BIKM1_LBM_Poisson(data$x,4,4,4,init_choice='smallVBayes')
icl=PoissonBlocICL(4,1,0.01,data$x,res@model_max$v,res@model_max$w, normalization=FALSE)

bikm1 documentation built on July 16, 2021, 9:08 a.m.