• 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