• DocumentCode
    3066277
  • Title

    Strongly-consistent nonparametric estimation of smooth regression functions for stationary ergodic sequences

  • Author

    Yakowitz, Sidney ; Györfi, László ; Kieffer, John ; Morvai, Gusztáv

  • Author_Institution
    Arizona Univ., USA
  • fYear
    1997
  • fDate
    29 Jun-4 Jul 1997
  • Firstpage
    402
  • Abstract
    Let {(Xi,Yi)} be a stationary ergodic Rd×R valued process. This study offers a strongly consistent (with respect to pointwise, least-squares, and uniform distance) algorithm for inferring the regression function E[Y0|X0=x], assumed uniformly Lipschitz continuous
  • Keywords
    estimation theory; functional analysis; nonparametric statistics; random processes; statistical analysis; least-squares algorithm; pointwise algorithm; random sequence; regression function; smooth regression functions; stationary ergodic sequences; strongly-consistent nonparametric estimation; uniform distance algorithm; uniformly Lipschitz continuous function; Informatics; Partitioning algorithms; Random sequences; Time series analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory. 1997. Proceedings., 1997 IEEE International Symposium on
  • Conference_Location
    Ulm
  • Print_ISBN
    0-7803-3956-8
  • Type

    conf

  • DOI
    10.1109/ISIT.1997.613339
  • Filename
    613339
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3066277