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)