Skip to main content

Maximum likelihood estimation of conditional logit models using Kernel Logistic Regression (KLR)

Project description

What is PyKernelLogit

PyKernelLogit is a Python package for performing maximum likelihood estimation of conditional logit models and similar discrete choice models based on the Python package PyLogit. This package extends the functionalities of PyLogit to provide some functionalities that allows to estimate discrete choice models based on Kernel Logistic Regression (KLR). Moreover, this package provides some functions to estimate indicators such as the Willingness to Pay (WTP) for the KLR models.


PyKernelLogit is available for its installation on the Python Package Index at:


PyKernelLogit was developed by José Ángel Martín Baos from the University of Castilla-La Mancha ( based on the package PyLogit ( developed by Timothy Brathwaite.


Modified BSD (3-clause)

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

pykernellogit-0.1.7.tar.gz (144.4 kB view hashes)

Uploaded Source

Built Distribution

pykernellogit-0.1.7-py3-none-any.whl (165.3 kB view hashes)

Uploaded Python 3

Supported by

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