This function computes univariate and multivariate Jarque-Bera tests and multivariate skewness and kurtosis tests for the residuals of a VAR(p) or of a VECM in levels.
normality.test(x, multivariate.only = TRUE)Object of class ‘varest’; generated by
VAR(), or an object of class ‘vec2var’;
generated by vec2var().
If TRUE (the default), only
multivariate test statistics are computed.
A list of class ‘varcheck’ with the following elements is
returned:
A matrix of the residuals.
A list of elements with class attribute
‘htest’ containing the univariate Jarque-Bera
tests. This element is only returned if multivariate.only =
FALSE is set.
A list of elements with class attribute
‘htest’.
Multivariate and univariate versions of the Jarque-Bera test are applied to the residuals of a VAR. The multivariate version of this test is computed by using the residuals that are standardized by a Choleski decomposition of the variance-covariance matrix for the centered residuals. Please note, that in this case the test result is dependant upon the ordering of the variables.
Hamilton, J. (1994), Time Series Analysis, Princeton University Press, Princeton.
Jarque, C. M. and A. K. Bera (1987), A test for normality of observations and regression residuals, International Statistical Review, 55: 163-172.
L<U+34AE5C2F>hl, H. (2006), New Introduction to Multiple Time Series Analysis, Springer, New York.
# NOT RUN {
data(Canada)
var.2c <- VAR(Canada, p = 2, type = "const")
normality.test(var.2c)
# }
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