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...
| Main Authors: | , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
American Scientific Publishers
2016
|
| Subjects: | |
| 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 |
| Summary: | 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. |
|---|