SUMMARY

This paper is concerned with the recursive estimation of autoregressive models, in particular the realtime determination of the order of such a specification. A model selection criterion based on the minimum description length principle due to Rissanen is discussed and strong consistency in the stationary situation is shown. Alternative criteria are also considered and modifications required to introduce forgetting when the procedures are implemented in the non-stationary case are presented. Some simulation evidence on the performance of the criteria when applied to stationary and non-stationary processes is given.

REFERENCES

1

Akaike
,
H.
(
1974
)
A new look at the statistical model identification
.
IEEE Trans. Auto. Contr.
,
19
,
716
723
.

2

Anderson
,
T. W.
(
1971
)
The Statistical Analysis of Time Series
, p.
247
.
New York
:
Wiley
.

3

Crochiere
,
R. E.
and
Flanagan
,
J. L.
(
1986
)
Speech processing: An evolving technology
.
AT&T Tech. J.
,
65
,
2
11
.

4

Friedlander
,
B.
(
1982
)
Lattice filters for adaptive processing
.
Proc. IEEE
,
70
,
829
867
.

5

Hannan
,
E. J.
and
Kavalieris
,
L.
(
1984
)
A method of autoregressive-moving average estimation
.
Biometrika
,
71
,
273
280
.

6

Hannan
,
E. J.
,
Kavalieris
,
L.
and
Mackisack
,
M.
(
1986
)
Recursive estimation of linear systems
.
Biometrika
,
73
,
119
133
.

7

Ljung
,
L.
and
Söderström
,
T.
(
1983
)
Theory and Practice of Recursive Identification.
Cambridge
:
Massachusetts Institute of Technology Press
.

8

Neveu
,
J.
(
1975
)
Discrete-parameter Martingales, proposition VII-2–4
.
New York
:
Academic Press
.

9

Poskitt
,
D. S.
and
Tremayne
,
A. R.
(
1987
)
Determining a portfolio of linear time series models
.
Biometrika
,
74
,
125
137
.

10

Rissanen
,
J.
(
1983
)
Universal prior for parameters and estimation by minimum description length
.
Ann. Statist.
,
11
,
416
431
.

11

Rissanen
,
J.
(
1986
)
Stochastic complexity and modeling
.
Ann. Statist.
,
14
,
1080
1100
.

12

Young
,
P. C.
(
1984
)
Recursive Estimation and Time Series Analysis.
Berlin
:
Springer
.

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