Bayesian Graphical Estimation using Spike-and-Slab Priors

Bayesian estimation for undirected graphical models using spike-and-slab priors. The package handles continuous, discrete, and mixed data.


News

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  • CHANGES IN VERSION 1.1

    • The sampling algorithms are implemented in C++ with parallel implementation using OpenMP.
    • Option "method" is added to function "ssgraph()" which is for both GGMs and GCGMs mehtods.
    • Functions "plot.ssgraph()", "summary.ssgraph()", and "print.ssgraph()" are added.
  • CHANGES IN VERSION 1.2

    • Option "save.all" is added to function "ssgraph()".
  • CHANGES IN VERSION 1.4

    • Option "is.discrete" is added to function "ssgraph()".
  • CHANGES IN VERSION 1.6

    • In function "ssgraph()", option "is.discrete" is changed to "not.cont".
    • "configure" and "configure.ac" are removed and "Makevars" and "Makevars.win" are modified accordingly.
  • CHANGES IN VERSION 1.7

    • In function "ssgraph()" option "save.all" is changed to "save".

Reference manual

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