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.


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    Title :

    Forecasting Using the Mahalanobis-Taguchi System in the Presence of Collinearity


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    SAE 2006 World Congress & Exhibition ; 2006



    Publication date :

    2006-04-03




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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