boxcoxmeta: Ensemble Based Box-Cox Transformation via Meta Analysis for...

In AID: Box-Cox Power Transformation

Ensemble Based Box-Cox Transformation via Meta Analysis for Normality of a Variable

Description

boxcoxmeta performs ensemble based Box-Cox transformation via meta analysis for normality of a variable and provides graphical analysis.

Usage

boxcoxmeta(data, lambda = seq(-3,3,0.01), nboot = 100, lambda2 = NULL, plot = TRUE, 
  alpha = 0.05, verbose = TRUE)

Arguments

data	a numeric vector of data values.
lambda	a vector which includes the sequence of candidate lambda values. Default is set to (-3,3) with increment 0.01.
nboot	a number of Bootstrap samples to estimate standard errors of lambda estimates.
lambda2	a numeric for an additional shifting parameter. Default is set to lambda2 = 0.
plot	a logical to plot histogram with its density line and qqplot of raw and transformed data. Defaults plot = TRUE.
alpha	the level of significance to check the normality after transformation. Default is set to alpha = 0.05.
verbose	a logical for printing output to R console.

Details

Denote y the variable at the original scale and y' the transformed variable. The Box-Cox power transformation is defined by:

y' = \left\{ \begin{array}{ll} \frac{y^\lambda - 1}{\lambda} \mbox{ , if $\lambda \neq 0$} \cr log(y) \mbox{ , if $\lambda = 0$} \end{array} \right.

If the data include any nonpositive observations, a shifting parameter \lambda_2 can be included in the transformation given by:

y' = \left\{ \begin{array}{ll} \frac{(y + \lambda_2)^\lambda - 1}{\lambda} \mbox{ , if $\lambda \neq 0$} \cr log(y + \lambda_2) \mbox{ , if $\lambda = 0$} \end{array} \right.

Value

A list with class "boxcoxmeta" containing the following elements:

method	name of method
lambda.hat	estimate of Box-Cox Power transformation parameter
lambda2	additional shifting parameter
result	a data frame containing the result
alpha	the level of significance to assess normality.
tf.data	transformed data set
var.name	variable name

Author(s)

Muhammed Ali Yilmaz, Osman Dag

References

Yilmaz, M.A., Dag, O. (2022). Ensemble Based Box-Cox Transformation via Meta Analysis. Journal of Advanced Research in Natural and Applied Sciences, 8:3, 463–471.

Examples

library(AID)
data(textile)

out <- boxcoxmeta(textile[,1])
out$lambda.hat # the estimate of Box-Cox parameter 
out$tf.data # transformed data set

AID documentation built on April 4, 2025, 1:53 a.m.