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MTSYS provides a collection of multivariate analysis methods in Mahalanobis-Taguchi System (MTS), which was developed for the field of quality engineering. MTS consists of two families depending on their purpose. One is a family of Mahalanobis-Taguchi (MT) methods (in the broad sense) for diagnosis and the other is a family of Taguchi (T) methods for forecasting.
The following methods are implemented.
For details, see the following referenses.
Install the release version from CRAN:
install.packages("MTSYS")
Or the development version from github
# install.packages("devtools")
devtools::install_github("okayaa/MTSYS")
library(MTSYS)
# 40 data for versicolor in the iris dataset
iris_versicolor <- iris[61:100, -5]
unit_space_MT <- MT(unit_space_data = iris_versicolor)
# 10 data for each kind (setosa, versicolor, virginica) in the iris dataset
iris_test <- iris[c(1:10, 51:60, 101:111), -5]
diagnosis_MT <- diagnosis(unit_space = unit_space_MT, newdata = iris_test,
threshold = 4)
(diagnosis_MT$le_threshold)
#> 1 2 3 4 5 6 7 8 9 10
#> FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
#> 51 52 53 54 55 56 57 58 59 60
#> TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
#> 101 102 103 104 105 106 107 108 109 110 111
#> TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
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