ivmodels 0.5.2

0.5.2 - 2024-10-03

Bug fixes:

• The Summary now correctly includes the rank and J test results.

ivmodels 0.5.1

0.5.1 - 2024-09-16

Bug fixes:

• Fixed the setuptools configuration.

ivmodels 0.5.0

0.5.0 - 2024-08-27

New features:

• The Wald test now supports robust covariance estimation.

• New method length for ConfidenceSet.

Other changes:

• One can now pass the tolerance parameter tol to the optimization algorithm in
  lagrange_multiplier_test and inverse_lagrange_multiplier_test via the kwargs.

• 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 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.

ivmodels 0.4.0

0.4.0 - 2024-08-08

New features:

• New test j_test of the overidentifying restrictions.

• The tests inverse_lagrange_multiplier_test and inverse_conditional_likelihood_ratio_test now possibly return unions of intervals, instead of one large conservative interval.

Bug fixes:

• Fixed bug in KClass.fit when C is not None and M_{[Z, C]} X is not full rank.

• Fixed bug ininverse_conditional_likelihood_ratio_test when k == mw + mx and C is not None.

• Fixed bug in utils._characteristic_roots if b == np.array([[0]]). This now correctly returns np.inf.

Other changes:

• The Summary now additionally reports the LIML variant of the J-statistic.

ivmodels 0.3.1

Bug fixes:

• Fixed bug in inverse_conditional_likelihood_ratio_test.

ivmodels 0.3.0

New features:

• New functions inverse_lagrange_multiplier_test and inverse_conditional_likelihood_ratio_test to approximate the 1 dimensional confidence sets by inverting the corresponding (subvector) tests.

• New classes ConfidenceSet

• New classes CoefficientTable, holding a table of coefficients and their p-values, and Summary, holding information about the model fit.

• The class KClass gets new attributes after fitting a model: endogenous_names_, exogenous_names_, and instrument_names_. If pandas is installed, there is also names_coefs_.

• The tests anderson_rubin_test, lagrange_multiplier_test, likelihood_ratio_test, and wald_test and their inverses inverse_anderson_rubin_test, inverse_lagrange_multiplier_test, inverse_likelihood_ratio_test, and inverse_wald_test now support an additional parameter D of exogenous covariates to be included in the test. This is not supported by the conditional likelihood ratio test.

Other changes:

• The function lagrange_multiplier_test is now slightly faster.

• The method KClass.fit now accepts pandas.Series as arguments to y.

ivmodels 0.2.0

New features:

• New method ivmodels.simulate.simulate_guggenberger12 to draw from the data
  generating process of Guggenberger (2012).

• The utility functions ivmodels.utils.proj and ivmodels.utils.oproj
  now accept multiple args to be projected. Usage of this results in performance
  improvements.

Other changes:

• The utility functions ivmodels.utils.proj and ivmodels.utils.oproj
  now use the scipy.linalg(..., lapack_driver="gelsy"). This results in a speedup.

• The numerical integration function
  ivmodels.tests.conditional_likelihood_ratio.conditional_likelihood_ratio_critical_value_function
  has been reparametrized, yielding a speedup.

ivmodels 0.1.0

Initial release