MTSYS (version 1.2.0)

MT: Function to generate a unit space for the Mahalanobis-Taguchi (MT) method

Description

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.

Usage

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

Arguments

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.

Value

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.

References

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.

See Also

solve, general_MT, generates_normalization_function, and diagnosis.MT

Examples

# NOT RUN {
# 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)

# }