A list with class "lg" containing the following elements:
method
method name
lambda2
additional shifting 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
Arguments
data
a numeric vector of data values.
lambda2
a numeric for an additional shifting parameter. Default is set to lambda2 = NULL.
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 Log power transformation is defined by:
$$y' = \log(y)$$
If the data include any nonpositive observations, a shifting parameter \(\lambda_2\) can be included in the transformation given by:
$$y' = \log(y+\lambda_2)$$
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.
Box, G.E., Cox, D.R. (1964). An Analysis of Transformations. Journal of the Royal Statistical Society: Series B (Methodological), 26:2, 211--43.
data <- cars$dist
library(Transform)
out <- lgTransform(data)
out$p.value # p.value of Shapiro-Wilk test for transformed data out$tf.data # transformed data set