Prediction Accuracies of Improved Taguchi's T Methods Compared to those of Multiple Regression Analysis

Abstract

Taguchi's T method belongs to the MT (Mahalanobis Taguchi) system. Several methods of MT system are used to detect outliers or extraordinary patterns, while the T method is used to predict future data. Since T method analyzes the same type of data set as the multiple regression analysis, the performance of T method has been compared with that of the multiple regression analysis under several case studies. This paper discusses the features of T method and considers two kinds of improved T methods. Furthermore, prediction accuracies of these methods are calculated by Monte Carlo simulations under several models. It is shown that the improved T methods are always superior to the original T method and that they are superior to the multiple regression analysis when the sample size is not large enough compared to the number of independent variables.