jarque.bera.test(x, fc = 3.5, ...)
Arima
.x
is not an Arima
object. See details.htest
object for the null hypothesis that
the kurtosis is $3$, the skewness is $0$ and a test combining
both the kurtosis and the skewness to test for the normality of the input data.jarque.bera.test
available in package The input can be a time series of residuals, jarque.bera.test.default
,
or an Arima
object, jarque.bera.test.Arima
from which the residuals
are extracted.
In the former case the whole input series of residuals is used.
In the latter case,
the first $n0$ (defined below) residuals are omitted if they are are equal to zero
or if any of them are in absolute value larger than fc
times
the standard deviation of the remaining residuals.
$n0$ is set equal to x$arma[6] + x$arma[5] * x$arma[7]
, i.e.
the number of regular differences times the periodicity of the data times
the number of seasonal differences. If $n0$ happens to be equal to $1$
it is set to $2$.
If the latter trimming operation is not desired,
the argument fc
can be set to a high value to ensure the complete
series of residuals in considered; or the function can be called
as jarque.bera.test(residuals(x))
.
Missing observations are omitted.
print.mhtest
.# fit an ARIMA model to the HICP 011600 series # ARIMA(0,1,0)(2,0,1) was chosen by forecast::auto.arima(ic = "bic") # normality of the residuals is rejected at the 5% significance level # due to an excess of kurtosis data("hicp") y <- log(hicp[["011600"]]) fit1 <- arima(y, order = c(0, 1, 0), seasonal = list(order = c(2, 0, 1))) jarque.bera.test(fit1) jarque.bera.test(residuals(fit1)) # fit ARIMA model for the same series including outliers that were # detected by "tsoutliers" and for the model chosen by "auto.arima" # normality of the residuals is not rejected at the 5% significance level # after including the presence of outliers mo <- outliers(c("AO", "AO", "LS", "LS"), c(79, 210, 85, 225)) xreg <- outliers.effects(mo, length(y)) fit2 <- arima(y, order = c(1, 1, 0), seasonal = list(order = c(2, 0, 2)), xreg = xreg) jarque.bera.test(fit2)
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