ssmodels 2.0.1
Bug Fixes
- Corrected the initialization of the
start
values in theHeckmanSK
function. Previously, it was relying on a two-step method to generate starting values, which could lead to numerical instability in some cases. Now, a more robust initialization is implemented to ensure better convergence and numerical stability. - Fixed the display of the log-likelihood in the
summary
methods of all functions (e.g.,summary.HeckmanSK
,summary.HeckmanCL
,summary.HeckmanBS
, etc.). Previously, these were reporting the negative of the log-likelihood. They now correctly display the log-likelihood value as returned by the optimization procedure.
ssmodels 2.0.0
CRAN release: 2025-06-01
Major updates
- Complete overhaul of the package, improving organization, readability, and performance of all functions.
- Rewritten log-likelihood and gradient functions (
loglik_*
andgradlik_*
) for enhanced numerical stability and clarity. - Fixed discrepancies where analytical gradients did not match numerical gradients.
- Comprehensive documentation updates for all functions, ensuring better understanding and usage.
- Added two new helper functions:
-
postprocess_theta()
: streamlines parameter transformations for clear interpretation and improved consistency across models. -
extract_model_components()
: extractsmodel.frame
,model.matrix
, andmodel.response
objects in a robust and reusable way.
-
- All functions now follow consistent coding style and best practices.
- Significant performance improvements, making the package lighter and more efficient.
ssmodels 1.0.1
CRAN release: 2022-10-04
Minor updates
- Improved documentation and examples.
- Added unit tests to ensure stability of
HeckmanCL()
and other core functions.
ssmodels 1.0.0
Initial release
- Initial implementation of the classic Heckman model (
HeckmanCL()
) and foundational sample selection models. - Basic infrastructure for selection bias correction in econometric models.