Transform (version 1.0)

glTransform: Glog Transformation for Normality

Description

glTransform performs Glog transformation for normality of a variable and provides graphical analysis.

Usage

glTransform(data, plot = TRUE, alpha = 0.05, verbose = TRUE)

Value

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

method

method name

statistic

Shapiro-Wilk test statistic for transformed data

p.value

Shapiro-Wilk test p.value for transformed data

alpha

level of significance to assess normality

tf.data

transformed data set

var.name

variable name

Arguments

data

a numeric vector of data values.

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.

Author

Muge Coskun Yildirim, Osman Dag

Details

Denote \(y\) the variable at the original scale and \(y'\) the transformed variable. The Glog power transformation is defined by:

$$y' = \log(y+ \sqrt{y^2+1})$$

References

Asar, O., Ilk, O., Dag, O. (2017). Estimating Box-Cox Power Transformation Parameter via Goodness of Fit Tests. Communications in Statistics - Simulation and Computation, 46:1, 91--105.

Durbin, B.P., Hardin, J.S., Hawkins, D.M., Rocke, D.M. (2002). A Variance-Stabilizing Transformation for Gene-expression Microarray Data. Bioinformatics, 18(suppl_1), 105--110.

Examples

data <- cars$dist

library(Transform)
out <- glTransform(data)
out$p.value # p.value of Shapiro-Wilk test for transformed data 
out$tf.data # transformed data set