PoissonBlocBIC {bikm1} R Documentation

## 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)


[Package bikm1 version 1.1.0 Index]