Metadata-Version: 1.0
Name: cde
Version: 0.5
Summary: Framework for conditional density estimation
Home-page: https://jonasrothfuss.github.io/Nonparametric_Density_Estimation
Author: Jonas Rothfuss, Fabio Ferreira
Author-email: jonas.rothfuss@gmx.de, fabioferreira@mailbox.org
License: MIT
Description: [![Build Status](https://travis-ci.org/ferreira-rothfuss/Conditional_Density_Estimation.svg?branch=master)](https://travis-ci.org/ferreira-rothfuss/Conditional_Density_Estimation)
        
        # Conditional Density Estimation (CDE)
        
        ## Description
        Implementations of various methods for conditional density estimation
        
        * **Parametric neural network based methods**
            * Mixture Density Networks (MDN)
            * Kernel Density Estimation (KMN)
        * **Nonparametric methods**
            * Conditional Kernel Density Estimation (CKDE)
            * $\epsilon$-Neighborhood Kernel Density Estimation (NKDE)
        * **Semiparametric methods**
            * Least Squares Conditional Density Estimation (LSKDE)
            
        Beyond estimating conditional probability densities, the package features extensive functionality for computing:
        * **Centered moments:** mean, covariance, skewness and kurtosis
        * **Statistical divergences:** KL-divergence, JS-divergence, Hellinger distance
        * **Percentiles and expected shortfall**
        
        ## Installation
        To use the library, either clone the GitHub repository and import it into your projects or install the pip package:
        ```
        pip install cde
        ```
        ## Documentation
        See the documentation [here](https://ferreira-rothfuss.github.io/Conditional_Density_Estimation).
        
        
        ## Citing
        If you use CDE in your research, you can cite it as follows:
        
        ```
        @misc{cde2019,
            author = {Jonas Rothfuss, Fabio Ferreira},
            title = {Conditional Density Estimation},
            year = {2019},
            publisher = {GitHub},
            journal = {GitHub repository},
            howpublished = {\url{https://github.com/ferreira-fabio/Conditional_Density_Estimation}},
        }
        ```
        
Platform: UNKNOWN
