Provides statistical tools for Bayesian structure learning in undirected graphical models for continuous, discrete, and mixed data. The package is implemented the recent improvements in the Bayesian graphical models literature, including Mohammadi and Wit (2015) <doi:10.1214/14-BA889>, Mohammadi et al. (2017) <doi:10.1111/rssc.12171>, and Dobra and Mohammadi (2018) <doi:10.1214/18-AOAS1164>. To speed up the computations, the BDMCMC sampling algorithms are implemented in parallel using OpenMP in C++.
|Author||Reza Mohammadi [aut, cre] <https://orcid.org/0000-0001-9538-0648>, Ernst Wit [aut], Adrian Dobra [ctb]|
|Maintainer||Reza Mohammadi <[email protected]>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
Install the latest version of this package by entering the following in R:
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.