Changelog
Source:NEWS.md
bml 0.9.0
Major Changes
Package renamed from
rmmtobml(Bayesian Multiple-Membership Multilevel Models)-
New syntax for weight functions: The
arparameter has been moved from thefn()specification to themm()block level for clearer API- Old:
fn(w ~ 1/n, c = TRUE, ar = FALSE) - New:
fn(w ~ 1/n, c = TRUE)withar = FALSEat themm()level
- Old:
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
coalgovdataset 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
arparameter moved: Existing code usingfn(w ~ ..., ar = TRUE)must be updated to placearin themm()block instead-
Dataset changes:
- Removed
schoolnetsdataset (includingnodedatandedgedatobjects) - Updated
coalgovdataset with enhanced documentation and additional variables
- Removed
Bug Fixes
Fixed issues with weight function constraints when using multiple
mm()blocksImproved handling of group-level indices in JAGS variable creation