Skip to main content

Compute the Kiefer-Wolfowitz nonparametric maximum likelihood estimator

Project description

Kiefer-Wolfowitz Nonparametric Empirical Bayes

Compute the Kiefer-Wolfowitz nonparametric maximum likelihood estimator for mixtures.

In contrast to the previous approaches, the optimization problem is reformulated into a convex problem by Koenker and Mizera (2014)'s method and efficiently solved by interior-point method.

Making Predictions With No Features - A Basic Usage

Given a training set T = {y_i}, the algorithm provides a way to construct a predictor of future y-values such that the sum of squared errors between observations and predictors is minimized.

Getting Started

Prerequisites

You will need:

  • python (>= 3.6)
  • pip (>= 19.0.3)
  • MOSEK (>=8.1.30)

Important about MOSEK:

  • MOSEK is a commercial optimization software. Please visit MOSEK for license information.
  • PIP:
pip install -f https://download.mosek.com/stable/wheel/index.html Mosek --user

For different ways of installation, please visit their installation page.

  • MOSEK needs to be installed in the GLOBAL environment.

Installing

pip install kwnpeb

Examples

  • simple - The basic usage
  • bayesball - In-season prediction of batting averages with the 2005 Major League baseball

Contributors

License

This project is licensed under the MIT License - see the LICENSE.md file for details

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

kwnpeb-0.1.11.tar.gz (3.4 kB view details)

Uploaded Source

Built Distribution

kwnpeb-0.1.11-py3-none-any.whl (4.5 kB view details)

Uploaded Python 3

File details

Details for the file kwnpeb-0.1.11.tar.gz.

File metadata

  • Download URL: kwnpeb-0.1.11.tar.gz
  • Upload date:
  • Size: 3.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.18.4 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.8

File hashes

Hashes for kwnpeb-0.1.11.tar.gz
Algorithm Hash digest
SHA256 137a274b3d992a0d715fe508c5a5127fc5a71489d1fd1a490528180d2af21538
MD5 f0ff7b193bf46580ac6ebe7f441bbfbb
BLAKE2b-256 be9537fecd17b6f962157096d5eb5cdfdf7bf171185ef2c45579bfe18a51ffc0

See more details on using hashes here.

File details

Details for the file kwnpeb-0.1.11-py3-none-any.whl.

File metadata

  • Download URL: kwnpeb-0.1.11-py3-none-any.whl
  • Upload date:
  • Size: 4.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.18.4 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.8

File hashes

Hashes for kwnpeb-0.1.11-py3-none-any.whl
Algorithm Hash digest
SHA256 15488fe8c9ff791f3dccf679bcfe61e33c01b388a8937005180963deff920a91
MD5 36e4ec4a67a9cfe28e5e297b78add984
BLAKE2b-256 7452f7b6a1dbe390fe4ce8fd6fecbe974f585d358efb658736e8d1301f2854f2

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page