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Changelog

Source: NEWS.md

bgms 0.1.4.3

New features

  • The bgmCompare function now allows for network comparison for two or more groups.
  • The new summary_sbm function can be used to summarize the output from the bgm function with the “Stochastic-Block” prior.

Other changes

  • The bgm function with the “Stochastic-Block” prior can now also return the sampled allocations and block probabilities, and sample and return the number of blocks.
  • The underlying R and c++ functions received a massive update to improve their efficiency and maintainance.

Bug fixes

  • Fixed a bug in the bgmCompare function with selecting group differences of blume-capel parameters. Parameter differences that were not selected and should be fixed to zero were still updated.
  • Fixed a bug in the bgmCompare function with handling the samples of blume-capel parameters. Output was not properly stored.
  • Fixed a bug in the bgmCompare function with handling threshold estimation when missing categories and main_model = “Free”. The sufficient statistics and number of categories were not computed correctly.

bgms 0.1.4.2

CRAN release: 2024-12-05

Fixed a bug with adjusting the variance of the proposal distributions. Fixed a bug with recoding data under the “collapse” condition. When selection = true, we run 2 * burnin iterations instead of 1 * burnin in the burnin phase. This helps ensure that the Markov chain used for estimating the pseudoposterior starts with good parameter values and that proposals are properly calibrated. In rare cases, the Markov chain could get stuck before. The default setting for the burnin is also changed from 1000 to 500. Changed the maximum standard deviation of the adaptive proposal from 20 back to 2.

bgms 0.1.4.1

CRAN release: 2024-11-12

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

bgms 0.1.4

CRAN release: 2024-10-20

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

CRAN release: 2024-02-25

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

CRAN release: 2023-10-13

This is a minor release that adds some bug fixes.

bgms 0.1.1

CRAN release: 2023-09-01

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.