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bootstrap(), kardl_longrun(),
mplier(), narayan(), pssf(),
psst(), and symmetrytest() are now implemented
as S3 methods for kardl_lm objects, with extended support
for kardl_longrun objects where appropriate.Added S3 methods for major kardl classes, improving
integration with standard R workflows.
Added summary() methods for:
kardl_testkardl_symmetricAdded dedicated print methods for:
kardl_decisionkardl_mplierIntroduced the new generic accessor function
kardl_extract() to retrieve documented components from
kardl objects without relying on internal object
structures.
Added extraction methods for:
kardl_mplierkardl_symmetrickardl_test_summaryallowing users to access multipliers, hypotheses, Wald test results, critical values, decisions, and other model components through a unified interface.
Standardized object output across kardl classes
using S3 methods.
Improved consistency of hypothesis reporting and decision summaries for cointegration and symmetry tests.
Enhanced printing of critical values, test statistics, and multiplier objects to better respect console width and improve readability.
kardl(formula, data)combineVarTypes() to
parse_model_specs().
parse_model_specs() is now exported to support developers
using kardl as a dependency for their own packages.parse_model_specs() (formerly
combineVarTypes):
CheckInputs().CheckInputs() remains an internal function and is not
exported.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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.