con-mrfse: Conservative approach for mrfse

Description Usage Arguments Value Author(s) References Examples

Description

Conservative construction of the estimated Markov random field graph.

Usage

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con.mrfse(a_size, sample, c, max_neigh = NULL)

Arguments

a_size

Size of the alphabet.

sample

A integer-valued matrix. Each value must belong range 0 and a_size - 1. Matrix has dimension n x V, where n is number of samples and V is number of nodes.

c

The penalization constant. Must be positive.

max_neigh

The maximum length of a candidate Markovian neighborhood. Must be non-negative and less than ncol(sample). If NULL then max_neigh will be set as ncol(sample) - 1.

Value

A adjacency matrix of the estimated Markov random field graph.

Author(s)

Rodrigo Carvalho

References

FRONDANA, Iara Moreira. Model selection for discrete Markov random fields on graphs. São Paulo : Instituto de Matemática e Estatística, University of São Paulo, 2016. Doctoral Thesis in Estatística. <doi:10.11606/T.45.2018.tde-02022018-151123> http://www.teses.usp.br/teses/disponiveis/45/45133/tde-02022018-151123/publico/tese_Iara_Frondana.pdf

Examples

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library(mrfse)
a = c(0, 1)
s = matrix(sample(a, size=1000, replace=TRUE), ncol=5)
con.mrfse(length(a), s, 1.0)

mrfse documentation built on April 2, 2020, 5:06 p.m.

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