Name
Abstract | ||
|---|---|---|
•Existing nonparametric frontier estimators tend to overfit data in the presence of moderate noise.•We propose new estimators with less overfitting.•Small sample properties of these estimators are provided in a Monte Carlo Simulation.•The simulation illustrates when the new estimators outperform the existing estimator. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.ejor.2017.07.057 | European Journal of Operational Research |
Keywords | Field | DocType |
Data envelopment analysis,Concave nonparametric frontier estimators,Stochastic DEA,Model averaging,Hinge functions | Econometrics,M-estimator,Mathematical optimization,Extremum estimator,Statistical noise,Bootstrapping (statistics),Nonparametric statistics,Data envelopment analysis,Overfitting,Statistics,Mathematics,Estimator | Journal |
Volume | Issue | ISSN |
264 | 3 | 0377-2217 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| ole bent olesen | 1 | 35 | 4.21 |
| John Ruggiero | 2 | 146 | 23.59 |