Non-Parametric Conditional <i>U</i>-Processes for Locally Stationary Functional Random Fields under Stochastic Sampling Design

Non-Parametric Conditional <i>U</i>-Processes for Locally Stationary Functional Random Fields under Stochastic Sampling Design

Stute presented the so-called conditional <i>U</i>-statistics generalizing the Nadaraya–Watson estimates of the regression function. Stute demonstrated their pointwise consistency and the asymptotic normality. In this paper, we extend the results to a more abstract setting. We develop an...

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Bibliographic Details
Main Authors: Salim Bouzebda, Inass Soukarieh
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Mathematics
Subjects:
conditional <i>U</i>-statistics
locally stationary random field
functional data
empirical processes
conditional <i>U</i>-processes
VC-class of functions
Online Access:https://www.mdpi.com/2227-7390/11/1/16

Internet

https://www.mdpi.com/2227-7390/11/1/16

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