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FBFsearch (version 1.2)

Algorithm for Searching the Space of Gaussian Directed Acyclic Graph Models Through Moment Fractional Bayes Factors

Description

We propose an objective Bayesian algorithm for searching the space of Gaussian directed acyclic graph (DAG) models. The algorithm proposed makes use of moment fractional Bayes factors (MFBF) and thus it is suitable for learning sparse graph. The algorithm is implemented by using Armadillo: an open-source C++ linear algebra library.

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Version

Install

install.packages('FBFsearch')

Monthly Downloads

206

Version

1.2

License

GPL (>= 2)

Maintainer

Davide Altomare

Last Published

August 8th, 2022

Functions in FBFsearch (1.2)

dataSim200

DAG model with 200 nodes and 100 edges
dataSim6

DAG model with 6 nodes and 5 edges
FBF_RS

Moment Fractional Bayes Factor Stochastic Search for Regression Models
FBF_GS

Moment Fractional Bayes Factor Stochastic Search with Global Prior for Gaussian DAG Models
dataPub

Publishing productivity data
dataSim100

DAG model with 100 nodes and 100 edges
dataSimHuman

Simulated cell signalling pathway data
dataHuman

Cell signalling pathway data
dataSim50

DAG model with 50 nodes and 100 edges
FBF_LS

Moment Fractional Bayes Factor Stochastic Search with Local Prior for DAG Models