Citing pyStoNED

If you use pyStoNED for published work, we encourage you to cite our pyStoNED paper and other related theoretical papers. Please use the following BibTeX entries:

• pyStoNED paper

@techreport{Dai2021,
    title    = {{pyStoNED: A Python package for convex regression and frontier estimation}},
    author   = {Dai, Sheng and Fang, Yu Hsueh and Lee, Chia Yen and Kuosmanen, Timo},
    year     = 2021,
    type     = {{arXiv preprint arXiv:2109.12962}}
}

• Theoretical papers

@article{Kuosmanen2008,
    title    = {{Representation theorem for convex nonparametric least squares}},
    year     = {2008},
    journal  = {Econometrics Journal},
    author   = {Kuosmanen, Timo},
    pages    = {308--325},
    doi      = {10.1111/j.1368-423X.2008.00239.x}
}

@article{Kuosmanen2010,
    title    = {{Data envelopment analysis as nonparametric least-squares regression}},
    year     = {2010},
    journal  = {Operations Research},
    author   = {Kuosmanen, Timo and Johnson, Andrew L.},
    pages    = {149--160},
    doi      = {10.1287/opre.1090.0722}
}

@article{Kuosmanen2012,
    title.   = {{Stochastic non-smooth envelopment of data: Semi-parametric frontier estimation subject to shape constraints}},
    year     = {2012},
    journal  = {Journal of Productivity Analysis},
    author   = {Kuosmanen, Timo and Kortelainen, Mika},
    pages    = {11--28},
    doi      = {10.1007/s11123-010-0201-3}
}

@article{Lee2013,
    title    = {{A more efficient algorithm for Convex Nonparametric Least Squares}},
    year     = {2013},
    journal  = {European Journal of Operational Research},
    author   = {Lee, Chia Yen and Johnson, Andrew L. and Moreno-Centeno, Erick and Kuosmanen, Timo},
    pages    = {391--400},
    doi      = {10.1016/j.ejor.2012.11.054},
}

@incollection{Ray2015,
    title    = {{An Introduction to CNLS and StoNED Methods for Efficiency Analysis: Economic Insights and Computational Aspects}},
    year     = {2015},
    booktitle= {Benchmarking for Performance Evaluation: A Production Frontier Approach},
    author   = {Johnson, Andrew L. and Kuosmanen, Timo},
    editor   = {Ray, Subhash C. and Kumbhakar, Subal C. and Dua, Pami},
    chapter  = {3},
    pages    = {117--186},
    publisher= {Springer}
}

@incollection{Kuosmanen2015,
    title    = {{Stochastic Nonparametric Approach to Efficiency Analysis: A unified Framework}},
    year     = {2015},
    booktitle= {Data Envelopment Analysis},
    author   = {Kuosmanen, Timo and Johnson, Andrew and Saastamoinen, Antti},
    editor   = {Zhu, Joe},
    chapter  = {7},
    pages    = {191–244},
    publisher= {Springer}
}