NEWS
mlmodels 0.1.2 (2026-05-08)
- Added return values in the documentation of exported functions that were missing them.
- Added references to implemented methods in the description.
mlmodels 0.1.1
- Fixed weighted log-likelihood calculation in
ml_logit() (both homoskedastic and heteroskedastic versions).
This bug previously caused incorrect log-likelihood, AIC, BIC, and convergence issues in weighted logit models.
- All other models were already handling weights correctly.
mlmodels 0.1.0
- First public release - Initial CRAN submission
- Provides maximum likelihood estimation for Gaussian (linear and log-normal), logit, probit, Poisson, negative binomial (NB1 and NB2), gamma, and beta models.
- Consistent S3 interface with support for modeling scale parameters.
- Multiple variance-covariance estimators (OIM, OPG, robust, cluster-robust, bootstrap, jackknife).
- Full suite of post-estimation tools and hypothesis tests.
- Compatible with
marginaleffects for marginal effects and predictions.
- Comprehensive vignettes covering main model families and diagnostics.