Recursive Computation of $M$-Estimates for the Parameters of a Finite Autoregressive Process
Campbell, Katherine
Ann. Statist., Tome 10 (1982) no. 1, p. 442-453 / Harvested from Project Euclid
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Stochastic approximation methods are used to generate a sequence of "$M$-estimates" for the unknown parameters of an autoregressive process of known, finite order which may have heavy-tailed innovations. Weak dependence properties, which can be demonstrated for many autoregressive processes, are used in the proof that the sequence converges almost surely to the parameters. A brief Monte Carlo study verifies that bounded influence functions provide protection for recursive procedures against heavy-tailed innovations.
Publié le : 1982-06-14
Classification:  Robustness,  stochastic approximation,  weak dependence,  62L12,  62M10,  62G35,  62L20 
@article{1176345785,
     author = {Campbell, Katherine},
     title = {Recursive Computation of $M$-Estimates for the Parameters of a Finite Autoregressive Process},
     journal = {Ann. Statist.},
     volume = {10},
     number = {1},
     year = {1982},
     pages = { 442-453},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1176345785}
}

Campbell, Katherine. Recursive Computation of $M$-Estimates for the Parameters of a Finite Autoregressive Process. Ann. Statist., Tome 10 (1982) no. 1, pp.  442-453. http://gdmltest.u-ga.fr/item/1176345785/