bgms 0.1.4.1

This is a minor release that adds some documentation and bug fixes.

bgms 0.1.4

New features

• Comparing the category threshold and pairwise interaction parameters in two independent samples with bgmCompare().
• The Stochastic Block model is a new prior option for the network structure in bgm().

Other changes

• Exported extractor functions to extract results from bgm objects in a safe way.
• Changed the maximum standard deviation of the adaptive proposal from 2 to 20.
• Some small bug fixes.

bgms 0.1.3

New features

• Added support for Bayesian estimation without edge selection to bgm().
• Added support for simulating data from a (mixed) binary, ordinal, and Blume-Capel MRF to mrfSampler()
• Added support for analyzing (mixed) binary, ordinal, and Blume-Capel variables to bgm()

User level changes

• Removed support of optimization based functions, mple(), mppe(), and bgm.em()
• Removed support for the Unit-Information prior from bgm()
• Removed support to do non-adaptive Metropolis from bgm()
• Reduced file size when saving raw MCMC samples

bgms 0.1.2

This is a minor release that adds some bug fixes.

bgms 0.1.1

This is a minor release adding some new features and fixing some minor bugs.

New features

• Missing data imputation for the bgm function. See the na.action option.
• Prior distributions for the network structure in the bgm function. See the edge_prior option.
• Adaptive Metropolis as an alternative to the current random walk Metropolis algorithm in the bgm function. See the adaptive option.

User level changes

• Changed the default specification of the interaction prior from UnitInfo to Cauchy. See the interaction_prior option.
• Changed the default threshold hyperparameter specification from 1.0 to 0.5. See the threshold_alpha and threshold_beta options.
• Analysis output now uses the column names of the data.