Data Envelopment Analysis , Principal Component Analysis , Non- Linear Programing Production Function , Frontier Function"/>, Open Access Library" />
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Prediction of A CRS Frontier Function and A Transformation Function for A CCR DEA Using EMBEDED PCAKeywords: Data Envelopment Analysis &searchField=keyword">"">Data Envelopment Analysis , Principal Component Analysis , Non- Linear Programing Production Function ,&searchField=keyword"> Frontier Function"/> Abstract: Data Envelopment Analysis is a nonparametric tool for measuring the performance of a number of homogenous Decision Making Units. In this paper, Principal Component Analysis is used as an alternative tool to estimate the frontier in a Data Envelopment Analysis under the assumption of Constant Return to Scale. Apart from this, in the context of a multiple inputs and single output, a transformation function, is developed here using the Most Productive Scale Size condition stated by Starrett. This function complies with all postulates of a frontier function and is very similar to the formula given by Aigner and Chu. Moreover, it is capable of defining the threshold value for any resource.
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