ar.gm(x, order=1, wsave=T, effgm=<<see below>>, effloc=<<see below>>,
b=T, c=<<see below>>, chr=<<see below>>, cbr=<<see below>>,
iterh=4, iterb=1)
TRUE, save wsmall; if
FALSE, save wbig.
0.87 or, if
c,
chr,
cbr, and/or
effloc are specified,
the value is determined by these constants.
If
effgm is specified, it determines the value of
c.
This is ignored if
iterh = iterb = 0.
effgm.
The default is
0.96 or, if
chr and
cbr are specified,
the value determined by them.
If
effloc is specified, it determines
chr and
cbr.
This is ignored if
iterh = iterb = 0.
TRUE, a bisquare is used; if
FALSE, a Huber is used.
4 or the value
determined by
effgm and
effloc if specified.
If both
effgm and
c are specified, the value specified for
effgm is used
to determine
c and the input
c is ignored.
1.5 or the value
determined by
effloc if
effloc is specified.
Input
chr is ignored if
effloc is specified.
The same
chr is used for the estimate of location used to center the data.
5
or the value determined by
effloc if
effloc is specified.
Input
cbr is ignored if
effloc is specified.
The same
cbr is used for the estimate of location.
iterh = 0 to do least squares.
iterb = 0 to do least squares.
order containing the gm estimates of the AR coefficients.
1
through
order.
order by
order estimated covariance matrix of the process.
x, the sample mean if
iterh = iterb = 0.
x, the standard deviation if
iterh = iterb = 0.
effgm.
effloc.
c.
chr.
chr, used in computing
Huber Proposal 2 scale estimates.
cbr.
cbr, used in computing
Huber Proposal 2 scale estimates.
wsave is
TRUE,
and wbig if
wsave is
FALSE.
Martin, R. D. (1980).
Robust estimation of autoregressive models.
In
Directions in Time Series.
D. R. Brillinger and G. C. Tiao, eds.
Institute of Mathematical Statistics, Hayward, Calif. pp. 228-254.
Martin, R. D. (1981).
Robust methods for time series.
In
Applied Time Series Analysis II.
D. F. Findley, ed. Academic Press, New York. pp. 683-759.
Time Series chapter.
robar <- ar.gm(bicoal.tons,2)