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Inférence par bootstrap×L'analyse enveloppante de données de réseau (Network DEA)×
DomaineStatistiqueAnalyse d'efficience
FamilleRegression modelRegression model
Année d'origine19792000
Auteur d'origineBradley EfronFäre & Grosskopf
TypeResampling-based inferenceMulti-stage nonparametric efficiency model
Source fondatriceEfron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26. DOI ↗Färe, R., & Grosskopf, S. (2000). Network DEA. Socio-Economic Planning Sciences, 34(1), 35–49. DOI ↗
Aliasbootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap ÇıkarımıNetwork Data Envelopment Analysis, Network Efficiency Analysis, Multi-Stage DEA, Ağ Veri Zarflama Analizi
Apparentées52
RésuméBootstrap inference, introduced by Bradley Efron in 1979, estimates the sampling distribution of a statistic by repeatedly resampling the observed data with replacement. It requires no distributional assumption and produces reliable confidence intervals even in small samples.Network Data Envelopment Analysis (Network DEA) is a nonparametric efficiency measurement framework introduced by Färe and Grosskopf (2000) that extends classical DEA to multi-stage or multi-division production processes. Rather than treating a decision-making unit as a black box, it explicitly models the internal structure — the divisions and the intermediate products that flow between them — enabling stage-level and overall efficiency scores to be estimated simultaneously within a single coherent model.
ScholarGateJeu de données
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ScholarGateComparer des méthodes: Bootstrap Inference · Network DEA. Consulté le 2026-06-17 sur https://scholargate.app/fr/compare