DocumentCode
3478671
Title
Model selection, stochastic complexity and badness amplification
Author
Gerencser, László ; Baikovicius, Jimmy
Author_Institution
Dept. of Electr. Eng., McGill Univ., Montreal, Que., Canada
fYear
1991
fDate
11-13 Dec 1991
Firstpage
1999
Abstract
The authors present a type of predictive stochastic complexity which penalizes overparametrization more heavily than its traditional counterparts. It forms the basis for a type of model order selection method for ARMA (autoregressive moving average) processes, which performs exceptionally well, as shown by extensive simulation results
Keywords
identification; statistical analysis; stochastic systems; ARMA processes; badness amplification; model order selection; overparametrization; statistical analysis; stochastic complexity; stochastic systems; Autoregressive processes; Complexity theory; Equations; Estimation theory; MIMO; Parameter estimation; Polynomials; Recursive estimation; Stochastic processes; Stochastic systems; Structural engineering;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 1991., Proceedings of the 30th IEEE Conference on
Conference_Location
Brighton
Print_ISBN
0-7803-0450-0
Type
conf
DOI
10.1109/CDC.1991.261768
Filename
261768
Link To Document