bgms 0.1.4
- Added bgmCompare() for comparing the category threshold and pairwise
interaction parameters in two independent samples.
- Added the Stochastic Block model as prior option for the network
structure.
- 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
- 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()
- 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.