On Sun, 27 Apr 2008, Allin Cottrell wrote:
> Moreover, we have an accessor ($h) only used for garch
> estimation, which does the same job as $sigma (which is unused
> for garch models), when you take into account that the estimate
> of the conditional variance is not a scalar but a series in
> these models by their very nature.
One point here: in the garch case $h gets the conditional
_variance_, not standard deviation, while $sigma gets the
unconditional or steady-state standard deviation. This is
unusual, but then garch is unusual; I'm not so sure it's
inconsistent.
True. But then, returning a covariance matrix is inconsistent too for
multivariate models (for consistency, we'd have to return a Cholesky
decomposition or something like that). Possibly, we could keep $h and
store in $sigma the time series of conditional std deviations, ie
sqrt($h).
Riccardo (Jack) Lucchetti
Dipartimento di Economia
Università Politecnica delle Marche
r.lucchetti(a)univpm.it
http://www.econ.univpm.it/lucchetti