On Adaptive Estimation in Stationary ARMA Processes
نویسندگان
چکیده
منابع مشابه
Bayesian Blind Estimation of H-ARMA Processes
We present a bayesian method for the blind estimation of parameters in nonlinear/nongaussian models. The studied models are called H-ARMA processes. They are generated by a memoryless polynomial transformation of an ARMA process. The nonlinearities are choosen as Her-mite polynomials. After recalling the structure of those models and their main properties that have been reported in previous pub...
متن کاملAdaptive Covariance Estimation of Locally Stationary Processes St
2 Locally Stationary Processes 2 2.1 Time-varying spectrum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.2 Locally stationary processes depending on a parameter . . . . . . . . . . . . 7 2.3 Local Cosine Approximations . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.4 Pseudo-di erential Covariance Operators . . . . . . . . . . . . . . . . . . . . 11 2.5 Time-Varying Fi...
متن کاملNonparametric Estimation for Stationary Processes
We consider the kernel density and regression estimation problem for a wide class of causal processes. Asymptotic normality of the kernel estimators is established under minimal regularity conditions on bandwidths. Optimal uniform error bounds are obtained without imposing strong mixing conditions. The proposed method is based on martingale approximations and provides a unified framework for no...
متن کاملEstimation in ARMA models based on signed ranks
In this paper we develop an asymptotic theory for estimation based on signed ranks in the ARMA model when the innovation density is symmetrical. We provide two classes of estimators and we establish their asymptotic normality with the help of the asymptotic properties for serial signed rank statistics. Finally, we compare our procedure to the one of least-squares, and we illustrate the performa...
متن کاملMinimum distance estimation of stationary and non-stationary ARFIMA processes
A new parametric minimum distance time-domain estimator for ARFIMA processes is introduced in this paper. The proposed estimator minimizes the sum of squared correlations of residuals obtained after filtering a series through ARFIMA parameters. The estimator is easy to compute and is consistent and asymptotically normally distributed for fractionally integrated (FI) processes with an integratio...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 1987
ISSN: 0090-5364
DOI: 10.1214/aos/1176350256