Release 4.12

Highlights of this release include:

• Dropping singleton observations in PanelOLS models
• Support for LSMR as an option to estimate parameters. LSMR can be much faster in very sparse unbalanced panels.
• Added wald_test to panel model results class.
• Added a low-memory option to limit memory usage when estimating models with 2 effects.

Release 4.11

This is primarily a bug-fix release. Two bugs which incorrectly verified rank conditions on models were fixed. These checks affected:

• All asset pricing models
• Fama-MacBeth panel data regression

In addition, an external dependency on cached-property was introduced.

Release 4.10

This is a bug-fix release that fixes an incorrect implementation of the Parzen weight function.
This release also contains small fixes for future changes in dependencies.

Release 4.9

This is a minor release that focuses on fixes for upstream changes.

• Changed the return type of Wooldridge's over identification test when
  invalid to InvalidTestStatistic
• Add typing information to IV models
• Allow optimization parameters to be passed to IVGMMCUE
• Removed internal use of pandas Panel
• Improved performance in panel models when using from_formula
• Switched to retaining index column names when original input index is named
• Modified tests that were not well conceived
• Added spell check to documentation build
• Improve docstring for summary properties

Release 4.8

This is a minor release with one feature and one bug fix:

• Corrected bug that prevented single character names in IV formulas
• Corrected kappa estimation in LIML when there are no exogenous regressors

Release 4.7

This is a minor release with one significant feature:

• Substantial performance improvements in PanelOLS and possibly other panel models for large dataset sizes

Linearmodels 4.6 release

• Add a license
• Change location of documentations

Linearmodels 4.5 release

• Added System GMM estimator
• Added automatic bandwidth for kernel-based GMM weighting estimators
• Cleaned up HAC estimation across models
• Added predict method to IV, Panel and System model to allow out-of-sample
  prediction and simplify retrieval of in-sample results
• Fixed small issues with Fama-MacBeth which previously ignored weights

Linearmodels 4.2 Release

New features:

• System estimation using GMM when there are endogenous variables
• General clean up of HAC estimators
• Many typos fixed

Linearmodels 4.1 Release

Minor release to address PyPi and documentation issues