Title :
Non-asymptotic bounds for autoregressive approximation
Author :
Goldenshluger, Alexander ; Zeevi, Assaf
Author_Institution :
Dept. of Stat., Haifa Univ., Israel
Abstract :
The subject of this paper is the autoregressive (AR) approximation of a stationary, Gaussian discrete time process, based on a finite sequence of observations. We adopt the nonparametric minimax framework and study how well can the process be approximated by a finite order autoregressive model
Keywords :
Gaussian processes; autoregressive processes; discrete time systems; information theory; minimax techniques; autoregressive approximation; finite order autoregressive model; finite sequence; nonasymptotic bounds; nonparametric minimax framework; stationary Gaussian discrete time process; Gaussian processes; Information systems; Least squares approximation; Least squares methods; Minimax techniques; Predictive models; Statistics; Stochastic processes; Transfer functions; Upper bound;
Conference_Titel :
Information Theory, 1998. Proceedings. 1998 IEEE International Symposium on
Conference_Location :
Cambridge, MA
Print_ISBN :
0-7803-5000-6
DOI :
10.1109/ISIT.1998.708909
