bml 0.9.0

Major Changes

• Package renamed from rmm to bml (Bayesian Multiple-Membership Multilevel Models)

• New syntax for weight functions: The ar parameter has been moved from the fn() specification to the mm() block level for clearer API

  • Old: fn(w ~ 1/n, c = TRUE, ar = FALSE)
  • New: fn(w ~ 1/n, c = TRUE) with ar = FALSE at the mm() level

• Support for multiple mmid groups: The package now supports models with multiple membership identifiers, allowing more complex membership structures

• Enhanced documentation: Comprehensive documentation added for the coalgov dataset including:

  • Detailed variable descriptions organized by level (identifiers, government-level, country-level, party-level)
  • Statistical summaries for all variables
  • Clear explanation of multiple-membership structure
  • Updated references and examples

New Features

• Flexible weight function parameterization: Enhanced support for parameterizing weight functions with covariates and group-specific structures

• Per-group random effects: Random effects can now be specified separately for different mmid groups

• Improved JAGS code generation: Optimized model string generation for better performance with complex multiple-membership structures

Breaking Changes

• ar parameter moved: Existing code using fn(w ~ ..., ar = TRUE) must be updated to place ar in the mm() block instead

• Dataset changes:

  • Removed schoolnets dataset (including nodedat and edgedat objects)
  • Updated coalgov dataset with enhanced documentation and additional variables

Bug Fixes

• Fixed issues with weight function constraints when using multiple mm() blocks

• Improved handling of group-level indices in JAGS variable creation

Documentation

• Updated vignette examples to use new syntax
• Added comprehensive FAQ section
• Improved installation instructions with CRAN and GitHub options
• Updated references to reflect 2026 publication

rmm 0.2.0

• Major syntax updates for weight function specification
• Improved prior specification interface
• Updated model string generation

rmm 0.1.1

• Removed posterior predictive p-values and fixed variance at second level for Weibull AFT regression

rmm 0.1.0

• Initial release
• Added a NEWS.md file to track changes to the package