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
fDate :
27 Jun-1 Jul 1994
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;
Conference_Titel :
Information Theory, 1994. Proceedings., 1994 IEEE International Symposium on
Conference_Location :
Trondheim
Print_ISBN :
0-7803-2015-8
DOI :
10.1109/ISIT.1994.395052
