The get_transform() gets transformation of numeric variable.
get_transform(
x,
method = c("log", "sqrt", "log+1", "log+a", "1/x", "x^2", "x^3", "Box-Cox",
"Yeo-Johnson")
)
numeric. numeric for transform
character. transformation method of numeric variable
numeric. transformed numeric vector.
The supported transformation method is follow.:
"log" : log transformation. log(x)
"log+1" : log transformation. log(x + 1). Used for values that contain 0.
"log+a" : log transformation. log(x + 1 - min(x)). Used for values that contain 0.
"sqrt" : square root transformation.
"1/x" : 1 / x transformation
"x^2" : x square transformation
"x^3" : x^3 square transformation
"Box-Cox" : Box-Box transformation
"Yeo-Johnson" : Yeo-Johnson transformation
# log+a transform
get_transform(iris$Sepal.Length, "log+a")
#> [1] 0.58778666 0.47000363 0.33647224 0.26236426 0.53062825 0.74193734
#> [7] 0.26236426 0.53062825 0.09531018 0.47000363 0.74193734 0.40546511
#> [13] 0.40546511 0.00000000 0.91629073 0.87546874 0.74193734 0.58778666
#> [19] 0.87546874 0.58778666 0.74193734 0.58778666 0.26236426 0.58778666
#> [25] 0.40546511 0.53062825 0.53062825 0.64185389 0.64185389 0.33647224
#> [31] 0.40546511 0.74193734 0.64185389 0.78845736 0.47000363 0.53062825
#> [37] 0.78845736 0.47000363 0.09531018 0.58778666 0.53062825 0.18232156
#> [43] 0.09531018 0.53062825 0.58778666 0.40546511 0.58778666 0.26236426
#> [49] 0.69314718 0.53062825 1.30833282 1.13140211 1.28093385 0.78845736
#> [55] 1.16315081 0.87546874 1.09861229 0.47000363 1.19392247 0.64185389
#> [61] 0.53062825 0.95551145 0.99325177 1.02961942 0.83290912 1.22377543
#> [67] 0.83290912 0.91629073 1.06471074 0.83290912 0.95551145 1.02961942
#> [73] 1.09861229 1.02961942 1.13140211 1.19392247 1.25276297 1.22377543
#> [79] 0.99325177 0.87546874 0.78845736 0.78845736 0.91629073 0.99325177
#> [85] 0.74193734 0.99325177 1.22377543 1.09861229 0.83290912 0.78845736
#> [91] 0.78845736 1.02961942 0.91629073 0.53062825 0.83290912 0.87546874
#> [97] 0.87546874 1.06471074 0.58778666 0.87546874 1.09861229 0.91629073
#> [103] 1.33500107 1.09861229 1.16315081 1.45861502 0.47000363 1.38629436
#> [109] 1.22377543 1.36097655 1.16315081 1.13140211 1.25276297 0.87546874
#> [115] 0.91629073 1.13140211 1.16315081 1.48160454 1.48160454 0.99325177
#> [121] 1.28093385 0.83290912 1.48160454 1.09861229 1.22377543 1.36097655
#> [127] 1.06471074 1.02961942 1.13140211 1.36097655 1.41098697 1.52605630
#> [133] 1.13140211 1.09861229 1.02961942 1.48160454 1.09861229 1.13140211
#> [139] 0.99325177 1.28093385 1.22377543 1.28093385 0.91629073 1.25276297
#> [145] 1.22377543 1.22377543 1.09861229 1.16315081 1.06471074 0.95551145
if (requireNamespace("forecast", quietly = TRUE)) {
# Box-Cox transform
get_transform(iris$Sepal.Length, "Box-Cox")
# Yeo-Johnson transform
get_transform(iris$Sepal.Length, "Yeo-Johnson")
} else {
cat("If you want to use this feature, you need to install the forecast package.\n")
}
<<<<<<< HEAD
#> Registered S3 method overwritten by 'quantmod':
#> method from
#> as.zoo.data.frame zoo
=======
>>>>>>> 2455413f029244b566a37aeed1916eea79ac483b
#> [1] 0.8361065 0.8305486 0.8246007 0.8214675 0.8333738 0.8437919 0.8214675
#> [8] 0.8333738 0.8148529 0.8305486 0.8437919 0.8276259 0.8276259 0.8113584
#> [15] 0.8529844 0.8507892 0.8437919 0.8361065 0.8507892 0.8361065 0.8437919
#> [22] 0.8361065 0.8214675 0.8361065 0.8276259 0.8333738 0.8333738 0.8387509
#> [29] 0.8387509 0.8246007 0.8276259 0.8437919 0.8387509 0.8461961 0.8305486
#> [36] 0.8333738 0.8461961 0.8305486 0.8148529 0.8361065 0.8333738 0.8182203
#> [43] 0.8148529 0.8333738 0.8361065 0.8276259 0.8361065 0.8214675 0.8413114
#> [50] 0.8333738 0.8750466 0.8649099 0.8734641 0.8461961 0.8667120 0.8507892
#> [57] 0.8630584 0.8305486 0.8684666 0.8387509 0.8333738 0.8551160 0.8571867
#> [64] 0.8591991 0.8485275 0.8701757 0.8485275 0.8529844 0.8611556 0.8485275
#> [71] 0.8551160 0.8591991 0.8630584 0.8591991 0.8649099 0.8684666 0.8718410
#> [78] 0.8701757 0.8571867 0.8507892 0.8461961 0.8461961 0.8529844 0.8571867
#> [85] 0.8437919 0.8571867 0.8701757 0.8630584 0.8485275 0.8461961 0.8461961
#> [92] 0.8591991 0.8529844 0.8333738 0.8485275 0.8507892 0.8507892 0.8611556
#> [99] 0.8361065 0.8507892 0.8630584 0.8529844 0.8765900 0.8630584 0.8667120
#> [106] 0.8837689 0.8305486 0.8795654 0.8701757 0.8780959 0.8667120 0.8649099
#> [113] 0.8718410 0.8507892 0.8529844 0.8649099 0.8667120 0.8851057 0.8851057
#> [120] 0.8571867 0.8734641 0.8485275 0.8851057 0.8630584 0.8701757 0.8780959
#> [127] 0.8611556 0.8591991 0.8649099 0.8780959 0.8809999 0.8876891 0.8649099
#> [134] 0.8630584 0.8591991 0.8851057 0.8630584 0.8649099 0.8571867 0.8734641
#> [141] 0.8701757 0.8734641 0.8529844 0.8718410 0.8701757 0.8701757 0.8630584
#> [148] 0.8667120 0.8611556 0.8551160