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 functi...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Published: |
2014
|
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1063/1.4903690 http://dx.doi.org/10.1063/1.4903690 http://umpir.ump.edu.my/7769/1/Computational_Efficiency_of_Generalized_Variance_and_Vector_Variance.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 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. |
|---|