v0.6.1 - 2021-02-25

This release improves the random_state functionality by taking in RandomState objects in addition to
random seeds.

General Improvements

• Use random_state instead of random_seed - Issue #113 by @katxiao

v0.6.0 - 2021-11-05

This release makes Copulas compatible with Python 3.9! It also improves library maintenance by
updating dependencies, reorganizing the CI workflows, adding pip check to the workflows and
removing unused files.

General Improvements

• Add support for Python 3.9 - Issue#282 by @amontanez24
• Remove entry point in setup.py - Issue#280 by @amontanez24
• Update pandas dependency range - Issue#266 by @katxiao
• Fix repository language - Issue#272 by @pvk-developer
• Add pip check to CI workflows - Issue#274 by @pvk-developer
• Reorganize workflows and add codecov - PR#267 by @csala
• Constrain jinja2 versions - PR#269 by @fealho

v0.5.1 - 2021-08-16

This release improves performance by changing the way scipy stats is used, calling their methods directly without creating intermediate instances.

It also fixes a bug introduced by the scipy 1.7.0 release where some distributions fail to fit because scipy validates the learned parameters.

Issues Closed

• Exception: Optimization converged to parameters that are outside the range allowed by the distribution. - Issue #264 by @csala
• Use scipy stats models directly without creating instances - Issue #261 by @csala

v0.5.0 - 2021-02-24

This release introduces conditional sampling for the GaussianMultivariate modeling.
The new conditioning feature allows passing a dictionary with the values to use to condition
the rest of the columns.

It also fixes a bug that prevented constant distributions to be restored from a dictionary
and updates some dependencies.

New Features

• Conditional sampling from Gaussian copula - Issue #154 by @csala

Bug Fixes

• ScipyModel subclasses fail to restore constant values when using from_dict - Issue #212 by @csala

v0.4.0 - 2021-01-27

This release introduces a few changes to optimize processing speed by re-implementing
the Gaussian KDE pdf to use vectorized root finding methods and also adding the option
to subsample the data during univariate selection.

General Improvements

• Make gaussian_kde faster - Issue #200 by @k15z and @fealho
• Use sub-sampling in select_univariate - Issue #183 by @csala

v0.3.3 (2020-09-18)

General Improvements

• Use corr instead of cov in the GaussianMultivariate - Issue #195 by @rollervan
• Add arguments to GaussianKDE - Issue #181 by @rollervan

New Features

• Log Laplace Distribution - Issue #188 by @rollervan

v0.3.2 (2020-08-08)

General Improvements

• Support Python 3.8 - Issue #185 by @csala
• Support scipy <1.3 - Issue #180 by @csala

New Features

• Add Uniform Univariate - Issue #179 by @rollervan

v0.3.1 (2020-07-09)

General Improvements

• Raise numpy version upper bound to 2 - Issue #178 by @csala

New Features

• Add Student T Univariate - Issue #172 by @gbonomib

Bug Fixes

• Error in Quickstarts : Unknown projection '3d' - Issue #174 by @csala

v0.3.0 (2020-03-27)

Important revamp of the internal implementation of the project, the testing
infrastructure and the documentation by Kevin Alex Zhang @k15z, Carles Sala
@csala and Kalyan Veeramachaneni @kveerama

Enhancements

• Reimplementation of the existing Univariate distributions.
• Addition of new Beta and Gamma Univariates.
• New Univariate API with automatic selection of the optimal distribution.
• Several improvements and fixes on the Bivariate and Multivariate Copulas implementation.
• New visualization module with simple plotting patterns to visualize probability distributions.
• New datasets module with toy datasets sampling functions.
• New testing infrastructure with end-to-end, numerical and large scale testing.
• Improved tutorials and documentation.

v0.2.5 - 2020-01-17

General Improvements

• Convert import_object to get_instance - Issue #114
  by @JDTheRipperPC