A Python Package for Stochastic Nonparametric Envelopment of Data
pyStoNED
pyStoNED is a Python package that provides functions for estimating Convex Nonparametric Least Square (CNLS), Stochastic Nonparametric Envelopment of Data (StoNED), and other various StoNED-related variants such as Convex Quantile Regression (CQR), Convex Expectile Regression (CER), and Isotonic CNLS (ICNLS). It also provides efficiency measurement using Data Envelopement Analysis (DEA) and Free Disposal Hull (FDH). The pyStoNED package allows the user to estimate the CNLS/StoNED frontiers in an open-access environment and is built based on the Pyomo.
The pyStoNED package is now avaiable on PyPI and the latest development version can be installed from the Github repository pyStoNED. Please feel free to download and test it. We welcome any bug reports and feedback.
PyPI
pip install pystoned
GitHub
pip install