View source: R/GoodnessOfFit.R
assess_transformation | R Documentation |
Not all data allows for a reasonable transformation to normality using power transformation. For example, uniformly distributed data or multi-modal data cannot be transformed to normality. This function computes a p-value for an empirical goodness of fit test for central normality. A distribution is centrally normal if the central 80% of the data are approximately normally distributed. The null-hypothesis is that the transformed distribution is centrally normal.
assess_transformation(x, transformer, verbose = TRUE, ...)
x |
A vector with numeric values that should be transformed to normality. |
transformer |
A transformer object created using
|
verbose |
Sets verbosity of the fubction. |
... |
Unused arguments. |
This function is a wrapper around ecn.test
.
p-value for empirical goodness of fit test.
x <- exp(stats::rnorm(1000))
transformer <- find_transformation_parameters(
x = x,
method = "box_cox")
assess_transformation(
x = x,
transformer = transformer)
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