BMN: The pseudo-likelihood method for pairwise binary markov networks

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This package implements approximate and exact methods for pairwise binary markov models. The exact method uses an implementation of the junction tree algorithm for binary graphical models. For more details see the help files

Author
Holger Hoefling
Date of publication
2010-04-25 16:00:14
Maintainer
Holger Hoefling <hhoeflin@gmail.com>
License
GPL-2
Version
1.02

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Man pages

BMNExact
Exact inference in L1-penalized Binary Markov Model
BMNExamples
Sampling data using Gibbs sampling for use in the examples
BMNJT
Junction tree algorithm for pairwise binary Markov networks
BMNPseudo
Pseudo-likelihood inference in L1-penalized Binary Markov...

Files in this package

BMN
BMN/R
BMN/R/BMNExact.R
BMN/R/BMNPseudo.R
BMN/R/SynDataGibbs.R
BMN/R/BMNJT.R
BMN/src
BMN/src/pseudoLikelihood.cc
BMN/src/Makevars.old
BMN/src/ProbGraph.cc
BMN/src/JTAlgWrapper.cc
BMN/src/pseudoLikelihood.h
BMN/src/Potential.cc
BMN/src/Potential.h
BMN/src/ProbGraph.h
BMN/src/Makevars.win
BMN/src/JunctionTree.h
BMN/src/JunctionTree.cc
BMN/src/Makevars
BMN/man
BMN/man/BMNExact.Rd
BMN/man/BMNExamples.Rd
BMN/man/BMNPseudo.Rd
BMN/man/BMNJT.Rd
BMN/DESCRIPTION
BMN/NAMESPACE