Applying the Mahalanobis-Taguchi System to Vehicle Ride

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 Mahalanobis-Taguchi System is of interest because of its reported accuracy in forecasting small, correlated data sets. This is the type of data that is encountered with consumer vehicle ratings. MTS enables a reduction in dimensionality and the ability to develop a scale based on MD values. MTS identifies a set of useful variables from the complete data set with equivalent correlation and considerably less time and data. This paper presents the application of the Mahalanobis-Taguchi System and its application to identify a reduced set of useful variables in multidimensional systems.

Department(s)

Engineering Management and Systems Engineering

Keywords and Phrases

Mahalanobis-Taguchi System; Data Set Forecasting; Diagnostic Methods

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2006 American Society of Mechanical Engineers (ASME), All rights reserved.

Publication Date

01 Nov 2006

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