heterogeneity | R Documentation |
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.
heterogeneity(x)
x |
a univariate time series |
A vector of numeric values.
Yanfei Kang and Rob J Hyndman
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