(Robust) Jarque Bera Test
This function performs the Jarque-Bera tests of normality either the robust or the classical way.
JarqueBeraTest(x, robust = TRUE, method = c("chisq", "mc"),
N = 0, na.rm = FALSE)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 |
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)).
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. |
This function is melted from the jarque.bera.test (in tseries package) and the rjb.test from the package lawstat.
W. Wallace Hui, Yulia R. Gel, Joseph L. Gastwirth, Weiwen Miao
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.
Alternative tests for normality as
shapiro.test,
AndersonDarlingTest, CramerVonMisesTest, LillieTest, PearsonTest, ShapiroFranciaTest
x <- rnorm(100) # null hypothesis JarqueBeraTest(x) x <- runif(100) # alternative hypothesis JarqueBeraTest(x, robust=TRUE)
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