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

Description Usage Arguments Value References See Also Examples

RT generates a unit space for the Recognition-Taguchi (RT) method. In general_MT, the inversed correlation matrix is used for A and the data are transformed by the function to be generated by generates_dimensionality_reduction_function based on unit_space_data. In the transformation, the p variables in unit_space_data are reduced into 2 synthetic variables.

1	RT(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.

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

`A`	2 x 2 matrix. Inversed correlation matrix of the transformed `unit_space_data`.
`calc_A`	`function(x) solve(cor(x), ...)`.
`transforms_data`	Function to be generated from `generates_dimensionality_reduction_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 always 2.
`x`	If `includes_transformed_data` is `TRUE`, then the transformed data are included.

Taguchi, G. (2006). Objective Function and Generic Function (11). Journal of Quality Engineering Society, 14(2), 5-9. (In Japanese)

Huda, F., Kajiwara, I., Hosoya, N., & Kawamura, S. (2013). Bolt loosening analysis and diagnosis by non-contact laser excitation vibration tests. Mechanical systems and signal processing, 40(2), 589-604.

solve, general_MT, generates_dimensionality_reduction_function, and diagnosis.MT

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

unit_space_RT <- RT(unit_space_data = iris_versicolor,
                    includes_transformed_data = TRUE)

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

(unit_space_RT$distance)