DocumentCode
2478105
Title
Non-asymptotic bounds for autoregressive approximation
Author
Goldenshluger, Alexander ; Zeevi, Assaf
Author_Institution
Dept. of Stat., Haifa Univ., Israel
fYear
1998
fDate
16-21 Aug 1998
Firstpage
304
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory, 1998. Proceedings. 1998 IEEE International Symposium on
Conference_Location
Cambridge, MA
Print_ISBN
0-7803-5000-6
Type
conf
DOI
10.1109/ISIT.1998.708909
Filename
708909
Link To Document