mlmodels 0.1.2
- 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.