R: (Robust) Jarque Bera Test

JarqueBeraTest {DescTools} | R Documentation

## (Robust) Jarque Bera Test

### Description

This function performs the Jarque-Bera tests of normality either the robust or the classical way.

### Usage

    JarqueBeraTest(x, robust = TRUE, method = c("chisq", "mc"),
                   N = 0, na.rm = FALSE)

### Arguments

`x` | a numeric vector of data values.
`robust` | defines, whether the robust version should be used. Default is `TRUE`.
`method` | a character string out of `chisq` or `mc`, specifying how the critical values should be obtained. Default is approximated by the chisq-distribution or empirically via Monte Carlo.
`N` | number of Monte Carlo simulations for the empirical critical values
`na.rm` | defines if `NAs` should be omitted. Default is `FALSE`.

### Details

The test is based on a joint statistic using skewness and kurtosis coefficients. The robust Jarque-Bera (RJB) version of utilizes the robust standard deviation (namely the mean absolute deviation from the median, as provided e. g. by `MeanAD(x, FUN=median)`) to estimate sample kurtosis and skewness. For more details see Gel and Gastwirth (2006).
Setting `robust` to `FALSE` will perform the original Jarque-Bera test (see Jarque, C. and Bera, A (1980)).

### Value

A list with class `htest` containing the following components:

`statistic` | the value of the test statistic.
`parameter` | the degrees of freedom.
`p.value` | the p-value of the test.
`method` | type of test was performed.
`data.name` | a character string giving the name of the data.

### Note

This function is melted from the `jarque.bera.test` (in `tseries` package) and the `rjb.test` from the package `lawstat`.

### Author(s)

W. Wallace Hui, Yulia R. Gel, Joseph L. Gastwirth, Weiwen Miao

### References

Gastwirth, J. L.(1982) Statistical Properties of A Measure of Tax Assessment Uniformity, Journal of Statistical Planning and Inference 6, 1-12.

Gel, Y. R. and Gastwirth, J. L. (2008) A robust modification of the Jarque-Bera test of normality, Economics Letters 99, 30-32.

Jarque, C. and Bera, A. (1980) Efficient tests for normality, homoscedasticity and serial independence of regression residuals, Economics Letters 6, 255-259.

### See Also

Alternative tests for normality as `shapiro.test`, `AndersonDarlingTest`, `CramerVonMisesTest`, `LillieTest`, `PearsonTest`, `ShapiroFranciaTest`

`qqnorm`, `qqline` for producing a normal quantile-quantile plot

### Examples

    x <- rnorm(100)    # null hypothesis
    JarqueBeraTest(x)

    x <- runif(100)    # alternative hypothesis
    JarqueBeraTest(x, robust=TRUE)

[Package DescTools version 0.99.26 Index]