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| 부트스트랩 추론× | 네트워크 자료포괄분석 (Network DEA)× | |
|---|---|---|
| 분야≠ | 통계학 | 효율성 분석 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1979 | 2000 |
| 창시자≠ | Bradley Efron | Färe & Grosskopf |
| 유형≠ | Resampling-based inference | Multi-stage nonparametric efficiency model |
| 원전≠ | Efron, 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 ↗ |
| 별칭 | bootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımı | Network Data Envelopment Analysis, Network Efficiency Analysis, Multi-Stage DEA, Ağ Veri Zarflama Analizi |
| 관련≠ | 5 | 2 |
| 요약≠ | Bootstrap 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. |
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