This paper continues the study of time series models generated by non-negative innovations which was begun in Feigin and Resnick (1992,1994). 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 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 : 1996-07-05
Classification:
Poisson processes,
linear programming,
autoregressive processes,
moving average processes,
parameter estimation,
weak convergence,
consistency,
time series analysis,
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST],
[STAT.TH]Statistics [stat]/Statistics Theory [stat.TH],
[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]
@article{hal-00179400,
author = {Kratz, Marie and Resnick, Sid and Feigin, Paul},
title = {Parameter estimation for moving averages with positive innovations.},
journal = {HAL},
volume = {1996},
number = {0},
year = {1996},
language = {en},
url = {http://dml.mathdoc.fr/item/hal-00179400}
}
Kratz, Marie; Resnick, Sid; Feigin, Paul. Parameter estimation for moving averages with positive innovations.. HAL, Tome 1996 (1996) no. 0, . http://gdmltest.u-ga.fr/item/hal-00179400/