Methods in Mahalanobis-Taguchi (MT) System
Function to calculate a cofactor matrix
Function to estimate M value (M hat) for a family of T methods.
Function to calculate overall prediction eta for the T method
Diagnosis method for the Mahalanobis-Taguchi (MT) method
Diagnosis method for the Mahalanobis-Taguchi Adjoint (MTA) method
Function to predict a diagnosis for a family of Mahalanobis-Taguchi (M...
Diagnosis method for the Recognition-Taguchi (RT) method
Function to predict a forecasting for a family of Taguchi (T) methods
Forecasting method for the T1 method
Forecasting method for the Ta method
Forecasting method for the Tb method
General function to implement a diagnosis method for a family of Mahal...
General function to implement a forecasting method for a family of Tag...
General function to generate a unit space for a family of Mahalanobis-...
General function to generate a prediction expression for a family of T...
Function to generate a data transformation function for the Recognitio...
Wrapper function to generate a model for a family of Taguchi (T) metho...
Function to generate the data normalization function
Function to generate data transformation functions for the T1 methods
Function to generate data transformation functions for the Tb methods
Wrapper function to generate a unit space for a family of Mahalanobis-...
Function to generate a unit space for the Mahalanobis-Taguchi (MT) met...
Function to generate a unit space for the Mahalanobis-Taguchi Adjoint ...
Function to generate a unit space for the Recognition-Taguchi (RT) met...
Function to generate a prediction expression for the two-sided Taguchi...
Function to generate a prediction expression for the Ta method
Function to generate a prediction expression for the Tb method
Mahalanobis-Taguchi (MT) system is a collection of multivariate analysis methods developed for the field of quality engineering. MT system consists of two families depending on their purpose. One is a family of Mahalanobis-Taguchi (MT) methods (in the broad sense) for diagnosis (see Woodall, W. H., Koudelik, R., Tsui, K. L., Kim, S. B., Stoumbos, Z. G., and Carvounis, C. P. (2003) <doi:10.1198/004017002188618626>) and the other is a family of Taguchi (T) methods for forecasting (see Kawada, H., and Nagata, Y. (2015) <doi:10.17929/tqs.1.12>). The MT package contains three basic methods for the family of MT methods and one basic method for the family of T methods. The MT method (in the narrow sense), the Mahalanobis-Taguchi Adjoint (MTA) methods, and the Recognition-Taguchi (RT) method are for the MT method and the two-sided Taguchi (T1) method is for the family of T methods. In addition, the Ta and Tb methods, which are the improved versions of the T1 method, are included.