diagnosis: Function to predict a diagnosis for a family of...

In okayaa/MT: Methods in Mahalanobis-Taguchi (MT) System

Description

diagnosis is a generic function. For details, see diagnosis.MT, diagnosis.MTA, diagnosis.RT or general_diagnosis.MT.

Usage

diagnosis(unit_space, newdata, threshold, includes_transformed_newdata)

Arguments

unit_space	Object generated as a unit space.
newdata	Matrix with n rows (samples) and p columns (variables). The data are used to calculate the desired distances from the unit space. All data should be continuous values and should not have missing values.
threshold	Numeric specifying the threshold value to classify each sample into positive (TRUE) or negative (FALSE).
includes_transformed_newdata	If TRUE, then the transformed data for newdata are included in a return object.

Value

A list containing the following components is returned.

distance	Vector with length n. Distances from the unit space to each sample.
le_threshold	Vector with length n. Logical values indicating the distance of each sample is less than or equal to the threhold value (TRUE) or not (FALSE).
threshold	Numeric value to classify the sample into positive or negative.
unit_space	Object passed by unit_space.
n	The number of samples for newdata.
q	The number of variables after the data transformation.
x	If includes_transformed_newdata is TRUE, then the transformed data for newdata are included.

See Also

diagnosis.MT, diagnosis.MTA, and diagnosis.RT

okayaa/MT documentation built on March 15, 2021, 8:41 a.m.