Salīdzināt metodes

	Logu Datu Aptveres Analīze	Tīkla datu apvalka analīze (Network DEA)
Nozare	Efektivitātes analīze	Efektivitātes analīze
Saime	Regression model	Regression model
Izcelsmes gads	1984	2000
Autors	Charnes, Clark, Cooper & Golany	Färe & Grosskopf
Tips	Non-parametric panel efficiency model	Multi-stage nonparametric efficiency model
Pirmavots	Charnes, A., Clark, C. T., Cooper, W. W., & Golany, B. (1984). A developmental study of data envelopment analysis in measuring the efficiency of maintenance units in the U.S. Air Forces. Annals of Operations Research, 2(1), 95–112.	Färe, R., & Grosskopf, S. (2000). Network DEA. Socio-Economic Planning Sciences, 34(1), 35–49.
Citi nosaukumi	Sliding-Window DEA, Temporal DEA, Rolling-Period DEA, Pencere VZA	Network Data Envelopment Analysis, Network Efficiency Analysis, Multi-Stage DEA, Ağ Veri Zarflama Analizi
Saistītās	2	2
Kopsavilkums	Window Data Envelopment Analysis (Window DEA) is a non-parametric panel efficiency method that evaluates decision-making units (DMUs) over time by embedding each DMU's observations across a rolling temporal window into a single cross-sectional DEA problem. Introduced by Charnes, Clark, Cooper, and Golany in 1984, it enables longitudinal efficiency tracking without requiring a full panel, increasing discriminatory power by pooling observations across consecutive periods.	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.