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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 These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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