Treatments of Non-metric Variables in Partial Least Squares and Principal Component Analysis

Jisu Yoon and Tatyana Krivobokova
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Jisu Yoon: Georg-August-University Göttingen
Tatyana Krivobokova: Georg-August-University Göttingen

No 172, Courant Research Centre: Poverty, Equity and Growth - Discussion Papers from Courant Research Centre PEG

Abstract: This paper reviews various treatments of non-metric variables in Partial Least Squares (PLS) and Principal Component Analysis (PCA) algorithms. The performance of different treatments is compared in the extensive simulation study under several typical data generating processes and recommendations are made. An application of PLS and PCA algorithms with non-metric variables to the generation of a wealth index is considered.

Keywords: Principal Component Analysis; PCA; Partial Least Squares; PLS; non-metric variables; simulation; wealth index (search for similar items in EconPapers)
JEL-codes: C15 C43 R20 (search for similar items in EconPapers)
Date: 2015-03-27
New Economics Papers: this item is included in nep-ecm
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Persistent link: https://EconPapers.repec.org/RePEc:got:gotcrc:172

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