Identifying the Influential Variable using Centrality Measure: A Case of Multivariate Time Series

Analysing the structure of multivariate system has been an important part in reliability analysis especially in identifying the influential variables. The complexity of the analysis increases when high dimensional data involved. To simplify the information in multivariate system, a network topology...

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Main Authors:	Nur Syahidah, Yusoff, Shamshuritawati, Sharif
Format:	Conference or Workshop Item
Language:	English English
Published:	American Scientific Publishers 2016
Subjects:	Q Science (General)
Online Access:	http://umpir.ump.edu.my/id/eprint/14012/ http://umpir.ump.edu.my/id/eprint/14012/1/Identifying%20the%20Influential%20Variable%20using%20Centrality.pdf http://umpir.ump.edu.my/id/eprint/14012/7/fist-2016-syahidah-Identifying%20the%20Influential%20Centrality.pdf

id	ump-14012
recordtype	eprints
spelling	ump-140122017-04-27T05:44:45Z http://umpir.ump.edu.my/id/eprint/14012/ Identifying the Influential Variable using Centrality Measure: A Case of Multivariate Time Series Nur Syahidah, Yusoff Shamshuritawati, Sharif Q Science (General) Analysing the structure of multivariate system has been an important part in reliability analysis especially in identifying the influential variables. The complexity of the analysis increases when high dimensional data involved. To simplify the information in multivariate system, a network topology which is based on an Escoufier’s RV-coefficient is constructed and centrality measure will be used to interpret the network. Statistically, RV-coefficient is a multivariate generalization of the squared Pearson correlation coefficient. An example in finance industry will be discussed to illustrate the structure of network topology and a recommendation will be presented. American Scientific Publishers 2016 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/14012/1/Identifying%20the%20Influential%20Variable%20using%20Centrality.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/14012/7/fist-2016-syahidah-Identifying%20the%20Influential%20Centrality.pdf Nur Syahidah, Yusoff and Shamshuritawati, Sharif (2016) Identifying the Influential Variable using Centrality Measure: A Case of Multivariate Time Series. In: Recent Research In Social Sciences International Conference (SOCSIC 2016), 31 May-2 June 2016 , Bandung, Indonesia. pp. 1-5..
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English English
topic	Q Science (General)
spellingShingle	Q Science (General) Nur Syahidah, Yusoff Shamshuritawati, Sharif Identifying the Influential Variable using Centrality Measure: A Case of Multivariate Time Series
description	Analysing the structure of multivariate system has been an important part in reliability analysis especially in identifying the influential variables. The complexity of the analysis increases when high dimensional data involved. To simplify the information in multivariate system, a network topology which is based on an Escoufier’s RV-coefficient is constructed and centrality measure will be used to interpret the network. Statistically, RV-coefficient is a multivariate generalization of the squared Pearson correlation coefficient. An example in finance industry will be discussed to illustrate the structure of network topology and a recommendation will be presented.
format	Conference or Workshop Item
author	Nur Syahidah, Yusoff Shamshuritawati, Sharif
author_facet	Nur Syahidah, Yusoff Shamshuritawati, Sharif
author_sort	Nur Syahidah, Yusoff
title	Identifying the Influential Variable using Centrality Measure: A Case of Multivariate Time Series
title_short	Identifying the Influential Variable using Centrality Measure: A Case of Multivariate Time Series
title_full	Identifying the Influential Variable using Centrality Measure: A Case of Multivariate Time Series
title_fullStr	Identifying the Influential Variable using Centrality Measure: A Case of Multivariate Time Series
title_full_unstemmed	Identifying the Influential Variable using Centrality Measure: A Case of Multivariate Time Series
title_sort	identifying the influential variable using centrality measure: a case of multivariate time series
publisher	American Scientific Publishers
publishDate	2016
url	http://umpir.ump.edu.my/id/eprint/14012/ http://umpir.ump.edu.my/id/eprint/14012/1/Identifying%20the%20Influential%20Variable%20using%20Centrality.pdf http://umpir.ump.edu.my/id/eprint/14012/7/fist-2016-syahidah-Identifying%20the%20Influential%20Centrality.pdf
first_indexed	2023-09-18T22:17:16Z
last_indexed	2023-09-18T22:17:16Z
_version_	1777415421038690304

Identifying the Influential Variable using Centrality Measure: A Case of Multivariate Time Series

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