Changes in version 0.1.3                        

  - Fixed a reproducibility bug where calling glemb() with an odd number
    of imputations (m) caused results to alternate between two distinct
    sets of imputations across successive calls with the same seed. The
    imputation step now uses R's own random number generator instead of
    the Fortran RNG in the mix package, whose internal state could not
    be fully reset between calls.

                        Changes in version 0.1.2                        

  - Added max.cells argument to glemb() (default 500000). A pre-flight
    check now stops with an informative error before glemb allocates any
    memory when the nominal variables would produce more cells than this
    limit. Set max.cells = Inf to disable the check.
  - Added meanmodel argument to glemb(). "main" (default) constrains the
    continuous variable means to depend only on the main effects of the
    categorical variables, reducing the number of mean parameters from
    n_cells to 1 + sum(K_j - 1). "saturated" restores the original
    cell-specific intercepts (unrestricted means).
  - The meanmodel value is stored in the returned object and displayed
    by print() and summary().

                        Changes in version 0.1.1                        

  - Added output = "mitml" option, returning a mitml.list object
    compatible with mitml::testEstimates().
  - Several bug fixes.

                        Changes in version 0.1.0                        

Initial release.

  - glemb(): multiple imputation for mixed continuous and categorical
    data using the General Location Model with the EMB algorithm.
  - Factor variables automatically treated as categorical; all other
    variables treated as continuous.
  - Log-linear model restricted to 2-way interactions by default; 3-way
    interactions available via cat.interact = 3.
  - Dirichlet prior on cell probabilities (cat.prior) for sparse-cell
    stabilisation.
  - Ridge prior on continuous covariance matrix (empri).
  - Output as list of completed data frames (default) or mids object
    compatible with mice::pool().
  - print() and summary() methods for glemb objects.