Mining Nonparametric Frontiers

José H. Dulá
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José H. Dulá: Virginia Commonwealth University

Chapter Chapter 9 in Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis, 2007, pp 155-170 from Springer

Abstract: Abstract Data envelopment analysis (DEA) is firmly anchored in efficiency and productivity paradigms. This research claims new application domains for DEA by releasing it from these moorings. The same reasons why efficient entities are of interest in DEA apply to the geometric equivalent in general point sets since they are based on the data’s magnitude limits relative to the other data points. A framework for non-parametric frontier analysis is derived from a new set of first principles. This chapter deals with the extension of data envelopment analysis to the general problem of mining oriented outliers.

Keywords: Data Envelopment Analysis (DEA); Linear Programming. (search for similar items in EconPapers)
Date: 2007
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DOI: 10.1007/978-0-387-71607-7_9

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