DocumentCode
2624605
Title
An algorithm for nonparametric forecasting for ergodic, stationary time series
Author
Yakowitz, Sidney ; Györfi, László ; Morvai, Gusztáv
Author_Institution
Dept. of Syst. & Ind. Eng., Arizona Univ., Tucson, AZ, USA
fYear
1994
fDate
27 Jun-1 Jul 1994
Firstpage
437
Abstract
The authors discuss doubly infinite stationary ergodic time series and sequences. The pattern recognition problem is considered as is the classification problem. Probabilities of misclassification and Bayes methods are mentioned
Keywords
Bayes methods; minimisation; pattern classification; prediction theory; sequences; time series; Bayes methods; algorithm; classification problem; doubly infinite stationary ergodic time series; ergodic stationary time series; misclassification probabilities; nonparametric forecasting; pattern recognition problem; sequences; Algebra; Computer industry; Computer science; Pattern recognition; Topology; USA Councils;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory, 1994. Proceedings., 1994 IEEE International Symposium on
Conference_Location
Trondheim
Print_ISBN
0-7803-2015-8
Type
conf
DOI
10.1109/ISIT.1994.395052
Filename
395052
Link To Document