Estimating production functions through additive models based on regression splines

Article Management

Random Forests and the measurement of super-efficiency in the context of Free Disposal Hull

Miriam Esteve et al.

Summary: This paper fills the research gap in the area of technical efficiency evaluation by applying Random Forest technique and solves the curse of dimensionality problem associated with the FDH method.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2023)

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Article Computer Science, Artificial Intelligence

Assesing the influence of environmental variables on the performance of water companies: An efficiency analysis tree approach

Maria Molinos-Senante et al.

Summary: This study experimented with a new efficiency assessment method called the Efficiency Analysis Tree (EAT). By employing a combination of classification, regression tree methods, and non-parametric analyses, this method overcomes the limitations of traditional approaches and provides a better evaluation of water company performance.

EXPERT SYSTEMS WITH APPLICATIONS (2023)

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Article Computer Science, Interdisciplinary Applications

Big data efficiency analysis: Improved algorithms for data envelopment analysis involving large datasets

Andreas Dellnitz

Summary: Data sets are growing larger, leading to big data concerns, including in data envelopment analysis (DEA). Improved decomposition-based algorithms are proposed to address the curse of dimensionality in DEA, with different termination criteria and multithreading introduced. The convergence of the algorithm is proven for some criteria, and extensive numerical analysis demonstrates the scalability of the algorithm.

COMPUTERS & OPERATIONS RESEARCH (2022)

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Article Management

The hinging hyperplanes: An alternative nonparametric representation of a production function.

O. B. Olesen et al.

Summary: In this paper, hinging hyperplanes (HHs) are proposed as a flexible nonparametric representation of a concave or an S-shaped production function. The HHs are derived using expressions focusing on the distinction between hinge location and bending. An estimation procedure is proposed where two HHs function approximations of the core function and the scaling law are estimated simultaneously. It is shown that HHs formulations provide global representations of all piecewise linear functional forms.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2022)

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Article Computer Science, Interdisciplinary Applications

Multi-output Support Vector Frontiers

Daniel Valero-Carreras et al.

Summary: This paper demonstrates how FDH and DEA can be seen as special cases of Support Vector Regression, introduces a robust concept of technical efficiency, and shows through computational experience that the new approach outperforms FDH and DEA in terms of performance.

COMPUTERS & OPERATIONS RESEARCH (2022)

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Article Engineering, Industrial

Efficiency estimation using probabilistic regression trees with an application to Chilean manufacturing industries

Mike Tsionas

Summary: This paper proposes smooth monotone concave probabilistic regression trees for the estimation of efficiency and productivity, and modifies these techniques to allow for the use of panel data commonly encountered in practice. Probabilistic regression trees provide smooth approximations and efficiently partition the space of regressors to approximate the unknown frontier, leveraging the versatility of standard regression trees. The new techniques are showcased in a large sample of Chilean manufacturing firms.

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS (2022)

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Article Management

Support vector frontiers: A new approach for estimating production functions through support vector machines

Daniel Valero-Carreras et al.

Summary: This paper introduces an improved method Support Vector Frontiers (SVF) in estimating production functions, which overcomes the overfitting issue and reduces bias associated with the estimation of the true production function. The research also suggests standard FDH and DEA can be reinterpreted as Support Vector Regression techniques.

OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE (2021)

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Efficiency analysis trees: A new methodology for estimating production frontiers through decision trees

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EXPERT SYSTEMS WITH APPLICATIONS (2020)

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THE INVERSE PROBLEM FOR HAMILTON-JACOBI EQUATIONS AND SEMICONCAVE ENVELOPES

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SIAM JOURNAL ON MATHEMATICAL ANALYSIS (2020)

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Efficiency evaluation based on data envelopment analysis in the big data context

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COMPUTERS & OPERATIONS RESEARCH (2018)

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Robust optimization in spline regression models for multi-model regulatory networks under polyhedral uncertainty

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OPTIMIZATION (2017)

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Modeling joint production of multiple outputs in StoNED: Directional distance function approach

Timo Kuosmanen et al.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2017)

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Generalized additive and index models with shape constraints

Yining Chen et al.

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY (2016)

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Data envelope fitting with constrained polynomial splines

Abdelaati Daouia et al.

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY (2016)

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A convex version of multivariate adaptive regression splines

Diana L. Martinez et al.

COMPUTATIONAL STATISTICS & DATA ANALYSIS (2015)

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A computational approach to nonparametric regression: bootstrapping CMARS method

Ceyda Yazici et al.

MACHINE LEARNING (2015)

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Model selection in multivariate adaptive regression splines (MARS) using information complexity as the fitness function

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MACHINE LEARNING (2015)

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Nonparametric quantile frontier estimation under shape restriction

Yongqiao Wang et al.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2014)

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RMARS: Robustification of multivariate adaptive regression spline under polyhedral uncertainty

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JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS (2014)

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Article Operations Research & Management Science

Restructuring forward step of MARS algorithm using a new knot selection procedure based on a mapping approach

Elcin Kartal Koc et al.

JOURNAL OF GLOBAL OPTIMIZATION (2014)

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Semi-parametric additive constrained regression

Mary C. Meyer

JOURNAL OF NONPARAMETRIC STATISTICS (2013)

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Estimating α-frontier technical efficiency with shape-restricted kernel quantile regression

Yongqiao Wang et al.

NEUROCOMPUTING (2013)

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Robust Estimation of Mean and Dispersion Functions in Extended Generalized Additive Models

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CMARS: a new contribution to nonparametric regression with multivariate adaptive regression splines supported by continuous optimization

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RCMARS: Robustification of CMARS with different scenarios under polyhedral uncertainty set

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COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION (2011)

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Evaluating the water sector in Italy through a two stage method using the conditional robust nonparametric frontier and multivariate adaptive regression splines

Francesco Vidoli

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2011)

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On the foundations of parameter estimation for generalized partial linear models with B-splines and continuous optimization

Pakize Taylan et al.

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Data Envelopment Analysis as Nonparametric Least-Squares Regression

Timo Kuosmanen et al.

OPERATIONS RESEARCH (2010)

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Nonparametric efficiency analysis: A multivariate conditional quantile approach

Abdelaati Daouia et al.

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Flexible and robust implementations of multivariate adaptive regression splines within a wastewater treatment stochastic dynamic program

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Nonparametric frontier estimation: A conditional quantile-based approach

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ECONOMETRIC THEORY (2005)

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A general methodology for bootstrapping in non-parametric frontier models

L Simar et al.

JOURNAL OF APPLIED STATISTICS (2000)

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Parallel MARS algorithm based on B-splines

S Bakin et al.

COMPUTATIONAL STATISTICS (2000)

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Estimating production functions through additive models based on regression splines

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