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Please use this identifier to cite or link to this item: http://hdl.handle.net/10525/1195

Title: An Approach to Variable Aggregation in Efficiency Analysis
Authors: Noncheva, Veska
Mendes, Armando
Silva, Emiliana
Keywords: Canonical Correlation Analysis
Data Envelopment Analysis
Efficiency
Variable Aggregation
Multivariate Statistics
Data Mining
Issue Date: 2009
Publisher: Institute of Information Theories and Applications FOI ITHEA
Abstract: In the nonparametric framework of Data Envelopment Analysis the statistical properties of its estimators have been investigated and only asymptotic results are available. For DEA estimators results of practical use have been proved only for the case of one input and one output. However, in the real world problems the production process is usually well described by many variables. In this paper a machine learning approach to variable aggregation based on Canonical Correlation Analysis is presented. This approach is applied for efficiency estimation of all the farms in Terceira Island of the Azorean archipelago.
URI: http://hdl.handle.net/10525/1195
ISSN: 1313-0455
Appears in Collections:Book 08 Classification Forecasting Data Mining

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