Description Usage Arguments Value Author(s)

Computes various measures of heterogeneity of a time series. First the series
is pre-whitened using an AR model to give a new series y. We fit a GARCH(1,1)
model to y and obtain the residuals, e. Then the four measures of heterogeneity
are:
(1) the sum of squares of the first 12 autocorrelations of *y^2*;
(2) the sum of squares of the first 12 autocorrelations of *e^2*;
(3) the *R^2* value of an AR model applied to *y^2*;
(4) the *R^2* value of an AR model applied to *e^2*.
The statistics obtained from *y^2* are the ARCH effects, while those
from *e^2* are the GARCH effects.

1 |

`x` |
a univariate time series |

A vector of numeric values.

Yanfei Kang and Rob J Hyndman

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