Title :
Large deviations for quadratic forms of Gaussian stationary processes with applications
Author :
Bercu, B. ; Gamboa, F. ; Rouault, A.
Author_Institution :
Lab. de Stat., Univ. de Paris-Sud, Orsay, France
Abstract :
We establish a large deviation principle for Toeplitz quadratic forms of stationary Gaussian processes. We also propose some statistical applications such as the large deviation behavior of the least squares and the Yule-Walker estimators of the parameter of the autoregressive stable Gaussian process
Keywords :
Gaussian processes; Toeplitz matrices; autoregressive processes; least squares approximations; parameter estimation; Gaussian stationary processes; Toeplitz quadratic forms; Yule-Walker estimators; autoregressive stable Gaussian process; large deviation behavior; least squares estimators; stationary Gaussian processes; Content addressable storage; Convergence; Eigenvalues and eigenfunctions; Gaussian processes; Least squares approximation; Level set; Parameter estimation; White noise;
Conference_Titel :
Decision and Control, 1997., Proceedings of the 36th IEEE Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4187-2
DOI :
10.1109/CDC.1997.650695
