A Comparative Study of Multivariate Analysis Techniques for Highly Correlated Variable Identification and Management
In this work we attempt is to locate and analyze via multivariate analysis techniques, highly correlated covariates (factors) which are interrelated with the Gross Domestic Product and therefore are affecting either on short-term or on long-term its shaping. For the analysis, feature selection techn...
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Format: | Article |
Language: | English |
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Ram Arti Publishers
2020-02-01
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Series: | International Journal of Mathematical, Engineering and Management Sciences |
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Online Access: | https://www.ijmems.in/volumes/volume5/number1/4-IJMEMS-19-565-51-4555-2020.pdf |
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author | K. Ntotsis E. N. Kalligeris A. Karagrigoriou |
author_facet | K. Ntotsis E. N. Kalligeris A. Karagrigoriou |
author_sort | K. Ntotsis |
collection | DOAJ |
description | In this work we attempt is to locate and analyze via multivariate analysis techniques, highly correlated covariates (factors) which are interrelated with the Gross Domestic Product and therefore are affecting either on short-term or on long-term its shaping. For the analysis, feature selection techniques and model selection criteria are used. The case study focuses on annual data for Greece for the period 1980-2018. |
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format | Article |
id | doaj.art-3db6d7339b2740d8a1be183e2a28afba |
institution | Directory Open Access Journal |
issn | 2455-7749 2455-7749 |
language | English |
last_indexed | 2024-04-13T17:02:07Z |
publishDate | 2020-02-01 |
publisher | Ram Arti Publishers |
record_format | Article |
series | International Journal of Mathematical, Engineering and Management Sciences |
spelling | doaj.art-3db6d7339b2740d8a1be183e2a28afba2022-12-22T02:38:36ZengRam Arti PublishersInternational Journal of Mathematical, Engineering and Management Sciences2455-77492455-77492020-02-0151455510.33889/IJMEMS.2020.5.1.004A Comparative Study of Multivariate Analysis Techniques for Highly Correlated Variable Identification and ManagementK. Ntotsis0E. N. Kalligeris1A. Karagrigoriou2Lab of Statistics and Data Analysis, Department of Statistics and Actuarial-Financial Mathematics, University of the Aegean, GreeceLab of Statistics and Data Analysis, Department of Statistics and Actuarial-Financial Mathematics, University of the Aegean, GreeceLab of Statistics and Data Analysis, Department of Statistics and Actuarial-Financial Mathematics, University of the Aegean, GreeceIn this work we attempt is to locate and analyze via multivariate analysis techniques, highly correlated covariates (factors) which are interrelated with the Gross Domestic Product and therefore are affecting either on short-term or on long-term its shaping. For the analysis, feature selection techniques and model selection criteria are used. The case study focuses on annual data for Greece for the period 1980-2018.https://www.ijmems.in/volumes/volume5/number1/4-IJMEMS-19-565-51-4555-2020.pdfmulticollinearitycorrelation feature selectionmodel selection criteriamultivariate analysisprincipal component analysis |
spellingShingle | K. Ntotsis E. N. Kalligeris A. Karagrigoriou A Comparative Study of Multivariate Analysis Techniques for Highly Correlated Variable Identification and Management International Journal of Mathematical, Engineering and Management Sciences multicollinearity correlation feature selection model selection criteria multivariate analysis principal component analysis |
title | A Comparative Study of Multivariate Analysis Techniques for Highly Correlated Variable Identification and Management |
title_full | A Comparative Study of Multivariate Analysis Techniques for Highly Correlated Variable Identification and Management |
title_fullStr | A Comparative Study of Multivariate Analysis Techniques for Highly Correlated Variable Identification and Management |
title_full_unstemmed | A Comparative Study of Multivariate Analysis Techniques for Highly Correlated Variable Identification and Management |
title_short | A Comparative Study of Multivariate Analysis Techniques for Highly Correlated Variable Identification and Management |
title_sort | comparative study of multivariate analysis techniques for highly correlated variable identification and management |
topic | multicollinearity correlation feature selection model selection criteria multivariate analysis principal component analysis |
url | https://www.ijmems.in/volumes/volume5/number1/4-IJMEMS-19-565-51-4555-2020.pdf |
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