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ssmodels 2.0.1

Bug Fixes

  • Corrected the initialization of the start values in the HeckmanSK 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_* and gradlik_*) 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(): extracts model.frame, model.matrix, and model.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.

Bug fixes

  • Fixed issues with incorrect gradient calculations for sigma and rho parameters.
  • Corrected numerical errors in several model functions.

Other improvements

  • Updated vignette and examples to reflect the new structure and improvements.
  • Switched pkgdown site to Bootstrap 5 for improved readability and responsiveness.

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.