Metadata-Version: 2.1
Name: PluginKernel
Version: 0.0.3
Summary: Plug-in Bandwidth Selection for Kernel Density Estimation with Discrete Data
Home-page: 
Author: Mehyar Mlaweh
Author-email: mehyarmlaweh0@gmail.com
License: MIT
Keywords: Kernel
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: Microsoft :: Windows :: Windows 10
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
License-File: LICENCE.txt

The Plugin library is a Python package designed to provide a simple and efficient way to perform kernel-based data analysis using the plugin algorithm. The plugin algorithm, proposed by P. Hall & Marron (1987) and extended by Park & Marron (1990), offers an iterative algorithm for the estimation of the optimal bandwidth parameter.
The plugin  utilizes an iterative algorithm to find the optimal smoothing parameter. The principle starts with a random choice of J(f), and subsequent evaluations of J(f) are deduced from the first value. Several iterations are performed to converge towards the optimal bandwidth parameter.






Change Log
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0.0.1 (13/08/2023)
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- First Release
