This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Forecasting Using the Mahalanobis-Taguchi System in the Presence of Collinearity
Technical Paper
2006-01-0502
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
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.
Authors
Topic
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.Also In
Reliability and Robust Design in Automotive Engineering, 2006
Number: SP-2032; Published: 2006-04-03
Number: SP-2032; Published: 2006-04-03
References
- Taguchi, G. Jugulum R. The Mahalanobis-Taguchi System: A Pattern Technology System John Wiley & Sons, Inc. 2002
- Woodall W.H. Koudelik R. Tsui K-L. Kim S.B. Stoumbos Z.G. Carvounis C.P. “A Review and Analysis of the Mahalanobis-Taguchi System” Technometrics February 2003 45 1 1 15
- Taguchi, S. “Mahalanobis Taguchi System” ASI Symposium 2000
- Lande, U. “Mahalanobis Distance: A Theoretical and Practical Approach” http://biologi.uio.no/fellesavdelinger/finse/spatialstats/Mahalanobis%20distance.ppt 2003
- Hayashi, S. Tanaka Y. Kodama E. “A New Manufacturing Control System using Mahalanobis Distance for Maximizing Productivity” IEEE Transactions 59 62 2001
- Asada, M. “Wafer Yield Prediction by the Mahalanobis-Taguchi System” IIE Transactions 25 28 2001
- Wu, Y. “Pattern Recognition using Mahalanobis Distance” TPD Symposium 1 14 1996
- Manly, B. Multivariate Statistical Methods Chapman & Hall 1994