Forecasting Using the Mahalanobis-Taguchi System in the Presence of Collinearity 2006-01-0502
The Mahalanobis Taguchi System is a diagnosis and forecasting method for multivariate data. Mahalanobis distance is a measure based on correlations between the variables and different patterns that can be identified and analyzed with respect to a base or reference group. The issue of multicollinearity is not adequately addressed in the MTS method. In cases where strong relationships exist between variables, the correlation matrix becomes almost singular and the inverse matrix is not accurate. Multicollinearity can be handled by utilizing the adjoint matrix of the correlation matrix and Gram-Schmidt orthogonalization. This paper presents a case study of the MTS methodology with the application of the adjoint matrix to avoid some effects of multicollinearity.
Citation: Cudney, E. and Ragsdell, K., "Forecasting Using the Mahalanobis-Taguchi System in the Presence of Collinearity," SAE Technical Paper 2006-01-0502, 2006, https://doi.org/10.4271/2006-01-0502. Download Citation
Author(s):
Elizabeth A. F. Cudney, Kenneth M. Ragsdell
Affiliated:
University of Missouri - Rolla
Pages: 8
Event:
SAE 2006 World Congress & Exhibition
ISSN:
0148-7191
e-ISSN:
2688-3627
Also in:
Reliability and Robust Design in Automotive Engineering, 2006-SP-2032
Related Topics:
Data management
Diagnostics
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