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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.

Installation

PyKernelLogit is available for its installation on the Python Package Index at: https://pypi.org/project/pykernellogit/.

Authors

PyKernelLogit was developed by José Ángel Martín Baos from the University of Castilla-La Mancha (JoseAngel.Martin@uclm.es) based on the package PyLogit (https://github.com/timothyb0912/pylogit) developed by Timothy Brathwaite.

License

Modified BSD (3-clause)

Project details


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Files for pykernellogit, version 0.1.6
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