Examining Data Homogeneity and Convexity for DEA Studies
碩士 === 國立交通大學 === 工業工程與管理系所 === 95 === Data quality is an important issue for all empirical studies including data envelopment analysis (DEA). Homogeneity and convexity are two fundamental assumptions for widely used DEA models such as BCC models (Banker et al., 1984) and CCR models (Charnes et al....
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ndltd-TW-095NCTU50310862016-05-04T04:16:29Z http://ndltd.ncl.edu.tw/handle/08811208343395342735 Examining Data Homogeneity and Convexity for DEA Studies 檢視DEA方法中之資料特性 郭晉嘉 碩士 國立交通大學 工業工程與管理系所 95 Data quality is an important issue for all empirical studies including data envelopment analysis (DEA). Homogeneity and convexity are two fundamental assumptions for widely used DEA models such as BCC models (Banker et al., 1984) and CCR models (Charnes et al., 1978). This study presents two methods to examine data homogeneity and convexity for DEA studies, respectively. Relying on well-known “leave-one-out” idea, a quantitative metric on the volume and surface area of a convex hull is adopted and implemented to detect outliers, which is non-homogeneous to the rest of others, from a given data set. The deviations between convexity based and non-convexity based models can be used to infer the shape of the production technology and examine the data convexity. 陳文智 2007 學位論文 ; thesis 70 en_US |
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碩士 === 國立交通大學 === 工業工程與管理系所 === 95 === Data quality is an important issue for all empirical studies including data envelopment analysis (DEA). Homogeneity and convexity are two fundamental assumptions for widely used DEA models such as BCC models (Banker et al., 1984) and CCR models (Charnes et al., 1978). This study presents two methods to examine data homogeneity and convexity for DEA studies, respectively. Relying on well-known “leave-one-out” idea, a quantitative metric on the volume and surface area of a convex hull is adopted and implemented to detect outliers, which is non-homogeneous to the rest of others, from a given data set. The deviations between convexity based and non-convexity based models can be used to infer the shape of the production technology and examine the data convexity.
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陳文智 |
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陳文智 郭晉嘉 |
author |
郭晉嘉 |
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郭晉嘉 Examining Data Homogeneity and Convexity for DEA Studies |
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郭晉嘉 |
title |
Examining Data Homogeneity and Convexity for DEA Studies |
title_short |
Examining Data Homogeneity and Convexity for DEA Studies |
title_full |
Examining Data Homogeneity and Convexity for DEA Studies |
title_fullStr |
Examining Data Homogeneity and Convexity for DEA Studies |
title_full_unstemmed |
Examining Data Homogeneity and Convexity for DEA Studies |
title_sort |
examining data homogeneity and convexity for dea studies |
publishDate |
2007 |
url |
http://ndltd.ncl.edu.tw/handle/08811208343395342735 |
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AT guōjìnjiā examiningdatahomogeneityandconvexityfordeastudies AT guōjìnjiā jiǎnshìdeafāngfǎzhōngzhīzīliàotèxìng |
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1718255000884346880 |