Generate constrained covariance matrix for a given graph to generate samples from a Gaussian graphical model using different algorithms for the analysis of complex network structure. We use three algorithms which are (1) Kim, K. I. et. al. (2008), <doi:10.1186/1471-2105-9-114> (2) IPF, Speed, T. et. al. (1986) <doi:10.1214/aos/1176349846>, (3) HTF, Hastie, T. et. al. (2009) <isbn: 9780387848570>.

Version: | 1.81 |

Depends: | R (≥ 2.12.0), igraph, mvtnorm, qpgraph (≥ 1.9.2) |

Imports: | Matrix, bnlearn, corpcor |

Published: | 2019-04-09 |

Author: | Shailesh Tripathi, Frank Emmert-Streib |

Maintainer: | Shailesh Tripathi <shailesh.tripathy at gmail.com> |

License: | GPL-2 |

NeedsCompilation: | no |

CRAN checks: | mvgraphnorm results |

Reference manual: | mvgraphnorm.pdf |

Vignettes: |
mvgraphnorm: An R package which generates constrained covariance matrix for a given graph to generate samples from a Gaussian graphical model |

Package source: | mvgraphnorm_1.81.tar.gz |

Windows binaries: | r-devel: mvgraphnorm_1.81.zip, r-devel-gcc8: mvgraphnorm_1.81.zip, r-release: mvgraphnorm_1.81.zip, r-oldrel: mvgraphnorm_1.81.zip |

OS X binaries: | r-release: not available, r-oldrel: not available |

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