Principal Components Analysis. Application to the Study of Risk-Factors for Social Dissociation on Territorial Level in Romania

Denis Enachescu; Cornelia Enachescu

doi:10.17713/ajs.v31i2&3.475

Principal Components Analysis. Application to the Study of Risk-Factors for Social Dissociation on Territorial Level in Romania

Authors

Denis Enachescu University of Bucharest
Cornelia Enachescu Center of Mathematical Statistics of the Romanian Academy

DOI:

https://doi.org/10.17713/ajs.v31i2&3.475

Abstract

The aim of the paper is to study simultaneously the whole set of data and point out the risk factors of the social dissociation on territorial level. Therefore, the authors used the Principal Components Analysis – PCA-techniques taking some socio-economic indicators for 1997 as variables and the counties of Romania as individuals. Finally, using the
factorial coordinates they classify the Romanian counties in nine different risk-classes.

References

C. Enachescu and D. Enachescu. Some Simple Rules for Interpreting Outputs of Principal Components and Correspondence Analysis. Anal. Univ. Buc., Informatics, XLIX:3-8, 2000.

L. Lebart, A. Morineau and M. Piron. Statistique exploratoire multidimensionnelle. Dunod, Paris, 1995.

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Published

2016-04-03

Issue

Vol. 31 No. 2&3 (2002)

Section

Articles

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How to Cite

Principal Components Analysis. Application to the Study of Risk-Factors for Social Dissociation on Territorial Level in Romania. (2016). Austrian Journal of Statistics, 31(2&3), 123-130. https://doi.org/10.17713/ajs.v31i2&3.475