generates_normalization_function: Function to generate the data normalization function
In MTSYS: Methods in Mahalanobis-Taguchi (MT) System

Description Usage Arguments Value See Also Examples

generates_normalization_function returns the data normalization function. The data normalization function is generated based on unit_space_data.

1 2	generates_normalization_function(unit_space_data, unit_space_center, unit_space_scale, is_scaled = TRUE)

`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.
`unit_space_center`	Vector with length p. The values are subtrahends in normalization. If missing, the mean for each column of `unit_space_data` is used for normalization.
`unit_space_scale`	Vector with length p. The values are divisors in normalization. If missing and `is_scaled` is `TRUE`, then the unbiased standard deviation for each column of `unit_space_data` is used for normalization.
`is_scaled`	Logical. If `TRUE` (default value), normalization is conducted by subtracting `unit_space_center` and dividing by `unit_space_scale`. If `FALSE`, normalization is conducted by subtracting `unit_space_center` only.

Function is returned which takes an n x p matrix as an (only) argument and returns a normalized n x p matrix. The normalization is conducted based on unit_space_data.

MT and MTA

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

normalizes_data <- generates_normalization_function(iris_versicolor)

is.function(normalizes_data) # TRUE