v0.2.2

This release includes

• a nice overhaul of the distributions backend by @BerriJ
• sanity checks for distribution and link function compatibility
• sanity checks for the distribution support
• some new docs for building new links and distributions
• more functionality for the debug mode by @simon-hirsch

v0.2.1

Improving the scaler:

• Allow for scaling of certain variables only. See https://simon-hirsch.github.io/rolch/scaler/ for details. You can now pass either a bool into scale_inputs or a numpy array with indices of the columns of $X$ you'd like to scale.

Some fixes:

• Add MLE estimates as start values to improve convergence in the beginning. This is more robust, since the previous start values might have been overly optimistic.
• Allow for boolean arrays in the equation and the scale_inputs.

v0.2.0

This release introduces the distinction between the Estimator() classes, which provides the .fit(), .update(), .predict() methods and the EstimationMethod() classes, which do the actual fitting of $X$, $y$ to coefficients / weights / betas. This gives

• easier integration of new estimation methods
• easier handling of default parameters for methods
• easier handling of non-default parameters for methods, especially for non-standard parameters like bounds, regularization strengths, etc..
• much cleaner code in OnlineGamlss()

Breaking change: This change gets rid of the estimation_kwargs parameter in OnlineGamlss() which was cumbersome and poorly documented anyways.

Furthermore, we

• align the API of OnlineGamlss() and OnlineLinearModel() and derive the OnlineLasso() from OnlineLinearModel() to show the flexibility of the new approach.
• Introduce a verbosity parameter for OnlineGamlss() to print information to the user.
• Add some properties to (slowly) align more to the sklearn API
• Some minor fixes like fixing #36
• Add a lot of documentation

v0.1.11

• Add OnlineLasso() Estimator to docs and ensure basic functionality
• Fix bugs in OnlineLasso()
• Add some link derivatives and second derivatives of link functions

v0.1.10

This release implements an important fix and does some maintenance and improvements in the backend.

Fixes

• Don't allow inversion of rank-deficit Gramian matrices - thanks to @katche1010 for spotting.

Improvements

• Allow batch updates of Gramian and Inverse Gramians
• Proper naming of links and their derivatives

v0.1.9 - Major API Improvements

This release implements a more structured API for model estimation. We introduce the equation dictionary, which specifies the model for each distribution parameter. Additionally, we fit intercepts for each distribution parameter per defaul now.

Fixes issues #23, #22 by @BerriJ, @simon-hirsch.

Much appreciated feedback on the API design by Franz Kiraly.

v0.1.8

• Added Gamma Distribution
• Improvements in the testing infrastructure
• Better handling of default values
• Some bugfixes

v0.1.5

Some bugfixes

v0.1.4: Fix rss calculation (#7)

• Improve / fix online model selection based on information criteria @BerriJ

v0.1.3

• Fix the model selection for LASSO
• Fix the weighted RSS calculation and updating
• Higher setuptools versions