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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.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.