DocumentCode
1343371
Title
Limits to consistent on-line forecasting for ergodic time series
Author
Györfi, Laszlo ; Morvai, Gusztav ; Yakowitz, Sidney J.
Author_Institution
Dept. of Math. & Comput. Sci., Tech. Univ. Budapest, Hungary
Volume
44
Issue
2
fYear
1998
fDate
3/1/1998 12:00:00 AM
Firstpage
886
Lastpage
892
Abstract
This article concerns problems of time-series forecasting under the weakest of assumptions. Related results are surveyed and are points of departure for the developments here, some of which are new and others are new derivations of previous findings. The contributions in this study are all negative, showing that various plausible prediction problems are unsolvable, or in other cases, are not solvable by predictors which are known to be consistent when mixing conditions hold
Keywords
nonparametric statistics; parameter estimation; prediction theory; random processes; time series; consistent on-line forecasting limits; dynamic forecasting; ergodic time series; mixing conditions; nonparametric estimation; prediction problems; random variable sequence; Books; Extrapolation; Gaussian processes; Interpolation; Kernel; Least squares approximation; Prediction theory; Random variables; Recursive estimation; Smoothing methods;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/18.661540
Filename
661540
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