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.ricest.ac.ir/dl/search/defaultta.aspx?DTC=49&DC=3066277
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