MT: Function to generate a unit space for the Mahalanobis-Taguchi...
In MTSYS: Methods in Mahalanobis-Taguchi (MT) System

Description Usage Arguments Value References See Also Examples

MT generates a unit space for the Mahalanobis-Taguchi (MT) method. In general_MT, the inversed correlation matrix is used for A and the data are normalized based on unit_space_data.

1	MT(unit_space_data, includes_transformed_data = FALSE, ...)

`unit_space_data`	Matrix with n rows (samples) and p columns (variables). Data to generate the unit space. All data should be continuous values and should not have missing values.
`includes_transformed_data`	If `TRUE`, then the transformed data are included in a return object.
`...`	Passed to `solve` for computing the inverse of the correlation matrix.

MT returns an object of S3 class "MT". An object of class "MT" is a list containing the following components:

`A`	p x p (q x q) matrix. Inversed correlation matrix of `unit_space_data` (the transformed data).
`calc_A`	`function(x) solve(cor(x), ...)`.
`transforms_data`	Function to be generated from `generates_normalization_function` based on `unit_space_data`.
`distance`	Vector with length n. Distances from the unit space to each sample.
`n`	The number of samples.
`q`	The number of variables after the data transformation. q is equal to p.
`x`	If `includes_transformed_data` is `TRUE`, then the transformed data are included.

Taguchi, G. (1995). Pattern Recognition and Quality Engineering (1). Journal of Quality Engineering Society, 3(2), 2-5. (In Japanese)

Taguchi, G., Wu, Y., & Chodhury, S. (2000). Mahalanobis-Taguchi System. McGraw-Hill Professional.

Taguchi, G., & Jugulum, R. (2002). The Mahalanobis-Taguchi strategy: A pattern technology system. John Wiley & Sons.

Woodall, W. H., Koudelik, R., Tsui, K. L., Kim, S. B., Stoumbos, Z. G., & Carvounis, C. P. (2003). A review and analysis of the Mahalanobis-Taguchi system. Technometrics, 45(1), 1-15.

solve, general_MT, generates_normalization_function, and diagnosis.MT

# 40 data for versicolor in the iris dataset
iris_versicolor <- iris[61:100, -5]

unit_space_MT <- MT(unit_space_data = iris_versicolor,
                    includes_transformed_data = TRUE)

# The following tol is a parameter passed to solve function.
unit_space_MT <- MT(unit_space_data = iris_versicolor,
                    includes_transformed_data = TRUE,
                    tol = 1e-9)

(unit_space_MT$distance)