Nonparametric regression estimation under mixing conditions

Nonparametric regression estimation under mixing conditions

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Article ID: iaor1991760
Country: Netherlands
Volume: 36
Issue: 1
Start Page Number: 107
End Page Number: 116
Publication Date: Oct 1990
Journal: Stochastic Processes and Their Applications
Authors:
Abstract:

For equ1 let equ2 be a strictly stationary sequence of random variables, where the X's and the Y's are equ3-valued and equ4-valued, respectively, for some integers p, equ5. Let equ6 be an integrable Borel real-valued function defined on equ7 and set equ8, equ9. The function equ10 need not be bounded. The quantity equ11is estimated by equ12where equ13is a kernel estimate for the probability density function equ14 of the X's and equ15. If the sequence equ16 enjoys any one of the standard four kinds of mixing properties, then, under suitable additional assumptions, equ17 is strongly consistent, uniformly over compacts. Rates of convergence are also specified.

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