fit {gRapHD}R Documentation

Log-likelihood, AIC, BIC

Description

Calculate -2*log-likelihood, AIC, and BIC for a triangulated graph (decomposable model).

Usage

  fit(model=NULL, edges=NULL, dataset, homog=TRUE)

Arguments

model gRapHD object.
edges matrix with 2 columns, each row representing one edge, and each column one of the vertices in the edge.
dataset matrix or data frame (nrow(dataset) observations and ncol(dataset) variables).
homog TRUE if the mixed model is homogeneous.

Value

Vector with: model dimension (no of free parameters), -2*log-likelihood, AIC, and BIC. Note that all parameters are assumed to be estimable in the dimension calculation.

Author(s)

Gabriel Coelho Goncalves de Abreu (Gabriel.Abreu@agrsci.dk)
Rodrigo Labouriau (Rodrigo.Labouriau@agrsci.dk)
David Edwards (David.Edwards@agrsci.dk)

Examples

  data(dsCont)
  m1 <- minForest(dsCont,homog=TRUE,forbEdges=NULL,stat="LR")
  fit(edges=m1$edges,dataset=dsCont)

[Package gRapHD version 0.1.0 Index]