Universal Schemes for Learning the Best Nonlinear Predictor Given the Infinite Past and Side Information
Universal Schemes for Learning the Best Nonlinear Predictor Given the Infinite Past and Side Information
复制标题
给定无限过去和辅助信息的情况下学习最佳非线性预测器的通用方案
DOI:
10.1109/18.761258
复制
发表时间:
1999
期刊:
影响因子:
--
通讯作者:
P. Algoet
中科院分区:
文献类型:
--
作者:
P. Algoet
Let {X/sub t/} be a real-valued time series. The best nonlinear predictor of X/sub 0/ given the infinite past X/sub -/spl infin///sup -1/ in the least squares sense, is equal to the conditional mean E{X/sub 0/|X/sub -/spl infin///sup -1/}. Previously, it has been shown that certain predictors based on growing segments of past observations converge to the best predictor given the infinite past whenever {X/sub t/} is a stationary process with values in a bounded interval. The present paper deals with universal prediction schemes for stationary processes with finite mean. We also discuss universal schemes for learning the conditional mean E{X/sub 0/|X/sub -/spl infin///sup -1/Y/sub -/spl infin///sup -1/Y/sub 0/} from past observations of a stationary pair process {(X/sub t/, Y/sub t/)}, and schemes for learning the repression function m(y)=E{X|Y=y} from independent samples of (X, Y).
DOI:
10.1002/9781118231296.ch8
发表时间:
2018-11
期刊:
Gauge Integral Structures for Stochastic Calculus and Quantum Electrodynamics
影响因子:
--
作者:
Dr. Gergely Záruba
通讯作者:
Dr. Gergely Záruba