O wykorzystaniu analizy głównych składowych w metodzie data envelopment analysis
About using principal component analysis in data envelopment analysis

Summary/Abstract: The article presents a comparison of two selected methods of PCA-DEA which are a connection of Principal Component Analysis (PCA) and Data Envelopment Analysis (DEA). The aim of PCA-DEA methods is to improve the results of a traditional DEA which discriminatory power weakens when the number of variables that describe objects increases and/or when the number of objects decreases. The results of a traditional DEA and PCA-DEA were compared in case of correct and too small group of studied objects. Real and simulated data sets were used.

• Details
• Contents