transformTukey: Tukey's Ladder of Powers

Description

Conducts Tukey's Ladder of Powers on a vector of values to produce a more-normally distributed vector of values.

Usage

transformTukey(
  x,
  start = -10,
  end = 10,
  int = 0.025,
  plotit = TRUE,
  verbose = FALSE,
  quiet = FALSE,
  statistic = 1,
  returnLambda = FALSE
)

Value

The transformed vector of values. The chosen lambda value is printed directly.

Arguments

x: A vector of values.
start: The starting value of lambda to try.
end: The ending value of lambda to try.
int: The interval between lambda values to try.
plotit: If TRUE, produces plots of Shapiro-Wilks W or Anderson-Darling A vs. lambda, a histogram of transformed values, and a quantile-quantile plot of transformed values.
verbose: If TRUE, prints extra output for Shapiro-Wilks W or Anderson-Darling A vs. lambda.
quiet: If TRUE, doesn't print any output to the screen.
statistic: If 1, uses Shapiro-Wilks test. Will report NA if the sample size is greater than 5000. If 2, uses Anderson-Darling test.
returnLambda: If TRUE, returns only the lambda value, not the vector of transformed values.

Author

Salvatore Mangiafico, mangiafico@njaes.rutgers.edu

Details

The function simply loops through lamdba values from start to end at an interval of int.

The function then chooses the lambda which maximizes the Shapiro-Wilks W statistic or minimizes the Anderson-Darling A statistic.

It may be beneficial to add a constant to the input vector so that all values are posititive. For left-skewed data, a (Constant - X) transformation may be helpful. Large values may need to be scaled.

References

https://rcompanion.org/handbook/I_12.html

Examples

Run this code

### Log-normal distribution example
Conc = rlnorm(100)
Conc.trans = transformTukey(Conc)

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