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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