Computational Efficiency of Generalized Variance and Vector Variance

• Main Authors: Shamshuritawati, Sharif, Wan Nur Syahidah, Wan Yusoff, Zurni, Omar, Suzilah, Ismail
• Format: Conference or Workshop Item
• Language: English
• Published: 2014
• Subjects: Q Science (General)
• Online Access: http://umpir.ump.edu.my/id/eprint/7769/1/Computational_Efficiency_of_Generalized_Variance_and_Vector_Variance.pdf; http://umpir.ump.edu.my/id/eprint/7769/; http://dx.doi.org/10.1063/1.4903690
• Institution: Universiti Malaysia Pahang

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.