Pages that link to "Item:Q1038415"

The following pages link to Improving discrimination in data envelopment analysis: PCA-DEA or variable reduction (Q1038415):

Displaying 30 items.

• Competition strategy and efficiency evaluation for decision making units with fixed-sum outputs (Q421570) (← links)
• Efficiency measurement using independent component analysis and data envelopment analysis (Q531456) (← links)
• On variable reductions in data envelopment analysis with an illustrative application to a gas company (Q670813) (← links)
• Multidimensional analysis of water sector performance in India: an index approach (Q831909) (← links)
• Comparison of variable selection techniques for data envelopment analysis in a retail bank (Q1751888) (← links)
• Economies of scope in the health sector: the case of Portuguese hospitals (Q1754138) (← links)
• Dimension reduction in nonparametric models of production (Q1754245) (← links)
• Combining uncertainty with uncertainty to get certainty? Efficiency analysis for regulation purposes (Q1755254) (← links)
• Review of methods for increasing discrimination in data envelopment analysis (Q1854786) (← links)
• Improving discrimination in data envelopment analysis without losing information based on Renyi's entropy (Q1989807) (← links)
• Methodology for calculating critical values of relevance measures in variable selection methods in data envelopment analysis (Q2029388) (← links)
• Variable selection in convex quantile regression: \(\mathcal{L}_1\)-norm or \(\mathcal{L}_0\)-norm regularization? (Q2083962) (← links)
• Bank efficiency and failure prediction: a nonparametric and dynamic model based on data envelopment analysis (Q2159559) (← links)
• Assessment of the technical efficiency of Brazilian logistic operators using data envelopment analysis and one inflated beta regression (Q2178377) (← links)
• Dealing with missing information in data envelopment analysis by means of low-rank matrix completion (Q2178379) (← links)
• Number of performance measures versus number of decision making units in DEA (Q2241198) (← links)
• Aggregation of inputs and outputs prior to data envelopment analysis under big data (Q2282502) (← links)
• Variable selection in data envelopment analysis (Q2282557) (← links)
• The curse of dimensionality of decision-making units: a simple approach to increase the discriminatory power of data envelopment analysis (Q2315646) (← links)
• APPLICATION OF PRINCIPAL COMPONENT ANALYSIS FOR PARSIMONIOUS SUMMARIZATION OF DEA INPUTS AND/OR OUTPUTS (Q4399702) (← links)
• Including principal component weights to improve discrimination in data envelopment analysis (Q4656715) (← links)
• A two-stage method for improving discrimination and variable selection in DEA models (Q5091798) (← links)
• Variables reduction in data envelopment analysis (Q5169453) (← links)
• (Q5446738) (← links)
• A note on DEA vs principal component analysis: An improvement to Joe Zhu's approach (Q5939586) (← links)
• Selecting slacks-based data envelopment analysis models (Q6112718) (← links)
• Evaluating different methods for ranking inputs in the context of the performance assessment of decision making units: a machine learning approach (Q6551089) (← links)
• Accuracy of deterministic nonparametric frontier models with undesirable outputs (Q6554659) (← links)
• Enhanced performance assessment of airlines with integrated balanced scorecard, network-based superefficiency DEA and PCA methods (Q6602069) (← links)
• Data envelopment analysis: from foundations to modern advancements (Q6640063) (← links)