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Data envelope fitting with constrained polynomial splines

Author

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  • Daouia, Abdelaati
  • Noh, Hohsuk
  • Park, Byeong U.

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Suggested Citation

  • Daouia, Abdelaati & Noh, Hohsuk & Park, Byeong U., 2016. "Data envelope fitting with constrained polynomial splines," LIDAM Reprints ISBA 2016011, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    • Handle: RePEc:aiz:louvar:2016011
    Note: In : Journal of the Royal Statistical Society. Series B, Statistical methodology, vol. 78, no.1, p. 3-30 (2016)
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    Cited by:

    1. Leonie Selk & Charles Tillier & Orlando Marigliano, 2022. "Multivariate boundary regression models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(1), pages 400-426, March.
    2. Raul Moragues & Juan Aparicio & Miriam Esteve, 2023. "Ranking the Importance of Variables in a Nonparametric Frontier Analysis Using Unsupervised Machine Learning Techniques," Mathematics, MDPI, vol. 11(11), pages 1-24, June.
    3. Natalie Neumeyer & Leonie Selk & Charles Tillier, 2020. "Semi-parametric transformation boundary regression models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(6), pages 1287-1315, December.
    4. Daouia, Abdelaati & Laurent, Thibault & Noh, Hohsuk, 2017. "npbr: A Package for Nonparametric Boundary Regression in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i09).
    5. Raul Moragues & Juan Aparicio & Miriam Esteve, 2023. "Measuring technical efficiency for multi-input multi-output production processes through OneClass Support Vector Machines: a finite-sample study," Operational Research, Springer, vol. 23(3), pages 1-33, September.
    6. España, Victor J. & Aparicio, Juan & Barber, Xavier & Esteve, Miriam, 2024. "Estimating production functions through additive models based on regression splines," European Journal of Operational Research, Elsevier, vol. 312(2), pages 684-699.

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