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 |

`method` |
a character string out of |

`N` |
number of Monte Carlo simulations for the empirical critical values |

`na.rm` |
defines if |

### 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)
```

*DescTools*version 0.99.55 Index]