CHANGELOG.rst

Changelog

0.5.2 - 2024-10-03

Bug fixes:

• The :class:`~ivmodels.summary.Summary` now correctly includes the rank and J test results.

0.5.1 - 2024-09-16

Bug fixes:

• Fixed the setuptools configuration.

0.5.0 - 2024-08-27

New features:

• The Wald test now supports robust covariance estimation.
• New method length for :class:`~ivmodels.confidence_set.ConfidenceSet`.

Other changes:

• One can now pass the tolerance parameter tol to the optimization algorithm in :func:`~ivmodels.tests.lagrange_multiplier.lagrange_multiplier_test` and :func:`~ivmodels.tests.lagrange_multiplier.inverse_lagrange_multiplier_test` via the kwargs.
• :class:`~ivmodels.models.kclass.KClass` now raises if kappa >= 1 (as for the LIML and TSLS estimators) and the number of instruments is less than the number of endogenous regressors.
• The :class:`~ivmodels.summary.Summary` now only includes and prints the results of the J-statistic and (multivariate) F-test for instrument strength if this makes sense.
• The docs have been updated and include examples.

0.4.0 - 2024-08-08

New features:

• New test :func:`~ivmodels.tests.j.j_test` of the overidentifying restrictions.
• The tests :func:`~ivmodels.tests.lagrange_multiplier.inverse_lagrange_multiplier_test` and :func:`~ivmodels.tests.conditional_likelihood_ratio.inverse_conditional_likelihood_ratio_test` now possibly return unions of intervals, instead of one conservative large interval.

Bug fixes:

• Fixed bug in :func:`~ivmodels.models.kclass.KClass.fit` when C is not None and M_{[Z, C]} X is not full rank.
• Fixed bug in :func:`~ivmodels.tests.conditional_likelihood_ratio.inverse_conditional_likelihood_ratio_test` when k == mw + mx and C is not None.
• Fixed bug in :func:`~ivmodels.utils._characteristic_roots` if b == np.array([[0]]). This now correctly returns np.inf.

Other changes:

• The :class:`~ivmodels.summary.Summary` now additionally reports the LIML variant of the J-statistic.

0.3.1 - 2024-07-30

Bug fixes:

• Fixed bug in :class:`~ivmodels.tests.conditional_likelihood_ratio.inverse_conditional_likelihood_ratio_test`.

0.3.0 - 2024-07-23

New features:

• New functions :func:`~ivmodels.tests.inverse_lagrange_multiplier_test` and :func:`~ivmodels.tests.inverse_conditional_likelihood_ratio_test` to approximate the 1 dimensional confidence sets by inverting the corresponding (subvector) tests.
• New class :class:`~ivmodels.confidence_sets.ConfidenceSet`.
• New class :class:`~ivmodels.summary.Summary` holding information about the model fit.
• New class :class:`~ivmodels.summary.CoefficientTable` holding a table of coefficients and their p-values.
• New method :func:`~ivmodels.models.kclass.KClass.summary` to create a summary of the model fit.
• The :class:`~ivmodels.models.kclass.KClass` gets new attributes after fitting a model: endogenous_names_, exogenous_names_, and instrument_names_. If pandas is installed, there's also names_coefs_.
• The tests :func:`~ivmodels.tests.anderson_rubin_test`, :func:`~ivmodels.tests.lagrange_multiplier_test`, :func:`~ivmodels.tests.likelihood_ratio_test`, and :func:`~ivmodels.tests.wald_test` and their inverses :func:`~ivmodels.tests.inverse_anderson_rubin_test`, :func:`~ivmodels.tests.inverse_lagrange_multiplier_test`, :func:`~ivmodels.tests.inverse_likelihood_ratio_test`, and :func:`~ivmodels.tests.inverse_wald_test` now support an additional parameter D of exogenous covariates to be included in the test. This is not supported for the conditional likelihood ratio test.

Other changes:

• The function :func:`~ivmodels.tests.lagrange_multiplier_test` is now slightly faster.
• :class:`~ivmodels.models.kclass.KClass` now accepts pandas.Series as arguments to y.

0.2.0 - 2024-06-07

New features:

• New method :func:`~ivmodels.simulate.simulate_guggenberger12` to draw from the data generating process of Guggenberger (2012).
• The utility functions :func:`~ivmodels.utils.proj` and :func:`~ivmodels.utils.oproj` now accept multiple args to be projected. Usage of this results in performance improvements.

Other changes:

• The utility functions :func:`~ivmodels.utils.proj` and :func:`~ivmodels.utils.oproj` now use the scipy.linalg(..., lapack_driver="gelsy"). This results in a speedup.
• The numerical integration function :func:`~ivmodels.tests.conditional_likelihood_ratio.conditional_likelihood_ratio_critical_value_function` has been reparametrized, yielding a speedup.