| bdTransform {Transform} | R Documentation | 
Bickel-Docksum Transformation for Normality
Description
bdTransform performs Bickel-Docksum transformation for normality of a variable and provides graphical analysis.  
Usage
bdTransform(data, lambda = seq(0.01,6,0.01), 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 (0.01,6) with increment 0.01. | 
| 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 Bickel-Docksum power transformation is defined by:
y' = \frac{|y|^\lambda Sign(y)-1}{\lambda} \mbox{ , if $\lambda > 0$} 
Value
A list with class "bd" containing the following elements:
| method | method to estimate Bickel-Docksum transformation parameter | 
| lambda.hat | estimate of Bickel-Docksum transformation parameter | 
| 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.
Bickel, P.J., Doksum, K.A. (1981). An Analysis of Transformations Revisited. Journal of the American Statistical Association, 76:374, 296–311.
Examples
data <- cars$dist
library(Transform)
out <- bdTransform(data)
out$lambda.hat # the estimate of Bickel-Docksum parameter based on Shapiro-Wilk test statistic 
out$p.value # p.value of Shapiro-Wilk test for transformed data 
out$tf.data # transformed data set