heterogeneity {tsfeatures} | R Documentation |
Heterogeneity coefficients
Description
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 ;
(2) the sum of squares of the first 12 autocorrelations of
;
(3) the
value of an AR model applied to
;
(4) the
value of an AR model applied to
.
The statistics obtained from
are the ARCH effects, while those
from
are the GARCH effects.
Usage
heterogeneity(x)
Arguments
x |
a univariate time series |
Value
A vector of numeric values.
Author(s)
Yanfei Kang and Rob J Hyndman
[Package tsfeatures version 1.1.1 Index]