sn_test {goft} | R Documentation |
Test for skew normality
Description
Transformation test of fit for skew-normality (Gonzalez-Estrada and Cosmes, 2019).
Usage
sn_test(x, method = "transf")
Arguments
x |
a numeric data vector containing a random sample of size n. |
method |
a character string giving the name of the test to be used. So far the only option is |
Details
The random sample is transformed to approximately normal variables. Shapiro-Wilk test is used for testing normality.
The sample size should be larger than 50 in order to have a reasonable control of the type I error probability.
Value
A list with class "htest"
containing the following components.
p.value |
an approximated p-value of the test. |
method |
the character string "Shapiro-Wilk test for skew-normal distributions". |
data.name |
a character string giving the name of the data set. |
Author(s)
Elizabeth Gonzalez-Estrada (egonzalez@colpos.mx)
References
Gonzalez-Estrada, E. and Cosmes, W. (2020). Shapiro-Wilk test for skew normal distributions based on data transformations. Journal of Statistical Computation and Simulation, 89 17, 3258-3272. https://doi.org/10.1080/00949655.2019.1658763
Examples
data(strength) # loading the "strength" data set
y <- strength$strain
sn_test(y) # testing skew normality on the strain variable