autotest example parsing (e.g., subscript out of bounds, recursive indexing failed). Updated example structures to be atomic and assignment-based, improving automated test generation and reproducibility.bootstrap() function now includes an optional seed argument, allowing users to set a random seed for reproducibility of bootstrap results.kardl_reset() function has been updated. Exclude argument is now optional and defaults to NULL, allowing users to reset all settings except those explicitly specified.\itemize{} vs \describe{}). Improved clarity and consistency across help pages.%>%) without proper imports, standalone expressions, and state-dependent workflows. Examples now follow a minimal and deterministic structure..) to improve compatibility with automated tools and standard R practices.@examplesIf, ensuring optional dependencies (e.g., magrittr, dplyr) do not break checks.summary() output has been corrected.Standard classes: All tests and estimation routines have been rewritten to use standard R classes such as htest, anova, and lm. This improves compatibility with generic methods and downstream analyses.
Multipliers & bootstrap: Added functionality to compute dynamic multipliers along with a bootstrap-based inference method, allowing more robust uncertainty quantification.
ECM method updated: The error correction model (ECM) method has been modified to enhance estimation accuracy and better integrate with the new class structure.
Internal improvements: Minor internal code improvements and documentation updates to support new features and maintain CRAN compliance.
Windows compatibility: Fixed an issue where the summary() output was not fully compatible with Windows in earlier versions.
Documentation: Updated documentation to reflect changes in function names and new features, ensuring clarity for users.
Examples: Updated examples in the documentation to demonstrate the new features and changes in function usage.
Testing: Added new unit tests to cover the new features and ensure the robustness of the package.
Performance: Improved performance of the estimation routines, particularly for larger datasets, through optimized code and better use of R's vectorized operations.
Error handling: Enhanced error handling to provide more informative messages when users encounter issues with input data or function usage.
Vignettes: Updated vignettes to include examples of the new features and to provide a comprehensive overview of the package's capabilities.