Jarque_Bera_test: Jarque-Bera Normality Test
Description
Performs the Jarque-Bera chi-squared test, a moment-based omnibus test for
assessing normality.
Usage
Jarque_Bera_test(
x,
alpha = 0.05,
alternative = c("two.sided", "less", "greater"),
silent = FALSE,
summary = TRUE
)Arguments
- x
Numeric vector. Must contain at least 20 observations.
- alpha
Numeric (default: 0.05). Significance level for hypothesis
testing. Must be between 0 and 1.
- alternative
Character (default: "two.sided"). Specifies the
alternative hypothesis. Available options are
c("two.sided", "less", "greater"). This argument applies only to the
skewness and kurtosis components and does not affect the Jarque-Bera
omnibus test statistic itself.
- silent
Logical (default: FALSE). If FALSE, results are printed
to the console.
- summary
Logical (default: TRUE). Produce a summary table.
Details
The test evaluates the null hypothesis that the data are drawn from a
normal distribution by combining standardized measures of skewness and
kurtosis into a single chi-squared test statistic.
References
Jarque, C.M., Bera, A.K., 1987.
A Test for Normality of Observations and Regression Residuals.
Int. Stat. Rev. 55, 163–172.
https://doi.org/10.2307/1403192
See Also
D.Agostino_Pearson_test()
Examples
Run this codeout <- Jarque_Bera_test(rnorm(50))
print(out$summary)
Run the code above in your browser using DataLab