| rpTransform {Transform} | R Documentation | 
Reciprocal Transformation for Normality
Description
rpTransform performs Reciprocal transformation for normality of a variable and provides graphical analysis.  
Usage
rpTransform(data, plot = TRUE, alpha = 0.05, verbose = TRUE)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. | 
Details
Denote y the variable at the original scale and y' the transformed variable. The Dual power transformation is defined by:
y' = \frac{1}{y}
Value
A list with class "rp" 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 | 
Author(s)
Muge Coskun Yildirim, Osman Dag
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.
Tukey, J.W. (1957). On the Comparative Anatomy of Transformations. The Annals of Mathematical Statistics, 602–32.
Examples
data <- cars$dist
library(Transform)
out <- rpTransform(data)
out$p.value # p.value of Shapiro-Wilk test for transformed data 
out$tf.data # transformed data set