This paper continues the study of time series models generated by
nonnegative innovations which was begun by Feigin and Resnick. We concentrate
on moving average processes. Estimators for moving average coefficients are
proposed and consistency and asymptotic distributions established for the case
of an order-one moving average assuming either the right or the left tail of
the innovation distribution is regularly varying. The rate of convergence can
be superior to that of the Yule-Walker or maximum likelihood estimators.
Publié le : 1996-11-14
Classification:
Poisson processes,
linear programming,
autoregressive processes,
moving average processes,
weak convergence,
consistency,
time series analysis,
60B10,
60F05,
60G55,
60E20,
26F10,
62M10
@article{1035463327,
author = {Feigin, Paul D. and Kratz, Marie F. and Resnick, Sidney I.},
title = {Parameter estimation for moving averages with positive
innovations},
journal = {Ann. Appl. Probab.},
volume = {6},
number = {1},
year = {1996},
pages = { 1157-1190},
language = {en},
url = {http://dml.mathdoc.fr/item/1035463327}
}
Feigin, Paul D.; Kratz, Marie F.; Resnick, Sidney I. Parameter estimation for moving averages with positive
innovations. Ann. Appl. Probab., Tome 6 (1996) no. 1, pp. 1157-1190. http://gdmltest.u-ga.fr/item/1035463327/