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arXiv · 2108.03582

Nonparametric Estimation of the Random Coefficients Model in Python

Emil Mendoza·Fabian Dunker·Marco Reale
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Abstract

We present $\textbf{PyRMLE}$, a Python module that implements Regularized Maximum Likelihood Estimation for the analysis of Random Coefficient models. $\textbf{PyRMLE}$ is simple to use and readily works with data formats that are typical to Random Coefficient problems. The module makes use of Python's scientific libraries $\textbf{NumPy}$ and $\textbf{SciPy}$ for computational efficiency. The main implementation of the algorithm is executed purely in Python code which takes advantage of Python's high-level features.

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Emil Mendoza, Fabian Dunker, Marco Reale. 2021-08-08. Nonparametric Estimation of the Random Coefficients Model in Python. https://arxiv.org/abs/2108.03582

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