ecn_test: Empirical central normality test

In power.transform: Location and Scale Invariant Power Transformations

Empirical central normality test

Description

Assesses central normality of input data using an empirical test. The test has the null hypothesis that the input data were sampled from a central normal distribution.

Usage

ecn_test(x = NULL, transformer = NULL, tau = NULL, n = NULL, kappa = 0.8)

Arguments

x	vector of input data, of at least length 5.
transformer	A transformer object created using find_transformation_parameters. Optional, if present residuals are determined from x after transformation.
tau	test statistic value. Usually computed from x, but if can be provided instead of x. tau cannot be negative.
n	number of samples. Usually the length of x, but can be provided directly with tau and kappa. n must be 5 or greater.
kappa	central portion of the distribution. For kappa = 1.0 the test is equivalent to a normality test, such as the Shapiro-Wilk test.

Value

list with the test statistic (tau), the critical value of the test statistic (at significance level = 0.95) (tau_critical) and p-value (p_value) for the empirical central normality test.

power.transform documentation built on Nov. 6, 2025, 1:10 a.m.