PoissonBlocBIC {bikm1}

PoissonBlocBIC function for the computation of the BIC criterion in the Poisson LBM

Description

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

Usage

PoissonBlocBIC(a,alpha,beta,v1,w1,x,res,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.

v1

a numeric vector of row partitions

w1

a numeric vector of column partitions

x

contingency matrix of observations.

res

a BIKM1_LBM_Poisson object rho_h mixing row proportions tau_l mixing column proportions gamma_hl Bernoulli parameters

normalization

logical. To use the normalized Poisson modelling in the Latent Block Model. By default normalization=FALSE.

Value

a value of the BIC 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,3,3,4,init_choice='smallVBayes')
bic=PoissonBlocBIC(v1=res@model_max$v,w1=res@model_max$w,x=data$x,res=res,normalization=TRUE)