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
fn(w ~ 1/n, c = TRUE, ar = FALSE)fn(w ~ 1/n, c = TRUE) with ar = FALSE
at the mm() levelSupport 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:
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
ar parameter moved: Existing code
using fn(w ~ ..., ar = TRUE) must be updated to place
ar in the mm() block instead
Dataset changes:
schoolnets dataset (including
nodedat and edgedat objects)coalgov dataset with enhanced documentation and
additional variablesFixed issues with weight function constraints when using multiple
mm() blocks
Improved handling of group-level indices in JAGS variable creation
NEWS.md file to track changes to the
package