Abstract
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. Copyright © 2006 SAE International.
Recommended Citation
E. A. Cudney and K. M. Ragsdell, "Forecasting using the Mahalanobis-Taguchi System in the Presence of Collinearity," SAE Technical Papers, SAE International, Jan 2006.
The definitive version is available at https://doi.org/10.4271/2006-01-0502
Department(s)
Engineering Management and Systems Engineering
International Standard Serial Number (ISSN)
2688-3627; 0148-7191
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 SAE International, All rights reserved.
Publication Date
01 Jan 2006
