Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/autocovariances.R

Carry out a test for GARCH white noise

1 | ```
acfGarchTest(acr, x, nlags, interval = 0.95)
``` |

`acr` |
autocorrelations. |

`x` |
time series. |

`nlags` |
how many lags to use. |

`interval` |
If not NULL, compute also confidence intervals with the specified coverage probability. |

`acfGarchTest`

performs a test for uncorrelatedness of a time
series. The null hypothesis is that the time series is GARCH,
see Francq \& Zakoian (2010).

Unlike the autocorrelation IID test, the time series is needed here to estimate the covariance matrix of the autocorrelations under the null hypothesis.

The format of the return vaue is the same as for `acfIidTest`

.

a list with components "test" and "ci"

Georgi N. Boshnakov

FrancqZakoian2010garchsarima

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | ```
## see also the examples for \code{\link{whiteNoiseTest}}
n <- 5000
x <- sarima:::rgarch1p1(n, alpha = 0.3, beta = 0.55, omega = 1, n.skip = 100)
x.acf <- autocorrelations(x)
x.pacf <- partialAutocorrelations(x)
acfGarchTest(x.acf, x = x, nlags = c(5,10,20))
acfGarchTest(x.pacf, x = x, nlags = c(5,10,20))
# do not compute CI's:
acfGarchTest(x.pacf, x = x, nlags = c(5,10,20), interval = NULL)
## plot methods call acfGarchTest() suitably if 'x' is given:
plot(x.acf, data = x)
plot(x.pacf, data = x)
## use 90% limits:
plot(x.acf, data = x, interval = 0.90)
``` |

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