Improving finite sample approximation by central limit theorems for estimates from Data Envelopment Analysis.
Léopold SimarValentin ZelenyukPublished in: Eur. J. Oper. Res. (2020)
Keyphrases
- limit theorems
- confidence intervals
- finite sample
- sample size
- data envelopment analysis
- input output
- dea models
- model selection
- linear programming
- heavy traffic
- error bounds
- multi criteria
- nearest neighbor
- upper bound
- statistical learning theory
- steady state
- dea model
- monte carlo
- vc dimension
- objective function
- neural network
- queue length
- statistical analysis
- markov chain
- support vector machine
- dynamic programming
- multi objective
- high dimensional