Computational efficiency of generalized variance and vector variance
In multivariate statistical quality control, the existing tests known as Generalized Variance (GV) and Vector Variance (VV), plays an important role in measuring process variability.In this paper, we present the computational efficiency of both tests to illustrate that their complexity as a function...
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2014
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my.uum.repo.152402016-05-25T08:12:26Z http://repo.uum.edu.my/15240/ Computational efficiency of generalized variance and vector variance Sharif, Shamshuritawati Wan Yusoff, Wan Nur Syahidah Omar, Zurni Ismail, Suzilah QA Mathematics In multivariate statistical quality control, the existing tests known as Generalized Variance (GV) and Vector Variance (VV), plays an important role in measuring process variability.In this paper, we present the computational efficiency of both tests to illustrate that their complexity as a function of dimension. From the mathematical derivation and simulation study, the computational efficiency of VV outperforms GV, particularly when the number of variables is large. 2014 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/15240/1/Com.pdf Sharif, Shamshuritawati and Wan Yusoff, Wan Nur Syahidah and Omar, Zurni and Ismail, Suzilah (2014) Computational efficiency of generalized variance and vector variance. In: International Conference on Quantitative Sciences and Its Applications (ICOQSIA 2014), 12–14 August 2014, Langkawi, Kedah Malaysia. http://doi.org/10.1063/1.4903690 doi:10.1063/1.4903690 |
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QA Mathematics Sharif, Shamshuritawati Wan Yusoff, Wan Nur Syahidah Omar, Zurni Ismail, Suzilah Computational efficiency of generalized variance and vector variance |
| description |
In multivariate statistical quality control, the existing tests known as Generalized Variance (GV) and Vector Variance (VV), plays an important role in measuring process variability.In this paper, we present the computational efficiency of both tests to illustrate that their complexity as a function of dimension. From the mathematical derivation
and simulation study, the computational efficiency of VV outperforms GV, particularly when the number of variables is
large. |
| format |
Conference or Workshop Item |
| author |
Sharif, Shamshuritawati Wan Yusoff, Wan Nur Syahidah Omar, Zurni Ismail, Suzilah |
| author_facet |
Sharif, Shamshuritawati Wan Yusoff, Wan Nur Syahidah Omar, Zurni Ismail, Suzilah |
| author_sort |
Sharif, Shamshuritawati |
| title |
Computational efficiency of generalized variance and vector variance |
| title_short |
Computational efficiency of generalized variance and vector variance |
| title_full |
Computational efficiency of generalized variance and vector variance |
| title_fullStr |
Computational efficiency of generalized variance and vector variance |
| title_full_unstemmed |
Computational efficiency of generalized variance and vector variance |
| title_sort |
computational efficiency of generalized variance and vector variance |
| publishDate |
2014 |
| url |
http://repo.uum.edu.my/15240/1/Com.pdf http://repo.uum.edu.my/15240/ http://doi.org/10.1063/1.4903690 |
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