A note on asymptotic normality of kernel estimation for linear random fields on Z 2

Tsung Lin Cheng; Hwai Chung Ho; Xuewen Lu

doi:10.1007/s10959-008-0146-x

A note on asymptotic normality of kernel estimation for linear random fields on Z ²

Tsung Lin Cheng, Hwai Chung Ho, Xuewen Lu

Graduate Institute of Statistics and Information Science

Research output: Contribution to journal › Article

5 Citations (Scopus)

Abstract

This note considers the kernel estimation of a linear random field on Z ². Instead of imposing certain mixing conditions on the random fields, it is assumed that the weights of the innovations satisfy a summability property. By building a martingale decomposition based on a suitable filtration, asymptotic normality is proven for the kernel estimator of the marginal density of the random field.

Original language	English
Pages (from-to)	267-286
Number of pages	20
Journal	Journal of Theoretical Probability
Volume	21
Issue number	2
DOIs	https://doi.org/10.1007/s10959-008-0146-x
Publication status	Published - 2008 Jun 1

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All Science Journal Classification (ASJC) codes

Statistics and Probability
Mathematics(all)
Statistics, Probability and Uncertainty

Cite this

Cheng, T. L., Ho, H. C., & Lu, X. (2008). A note on asymptotic normality of kernel estimation for linear random fields on Z ². Journal of Theoretical Probability, 21(2), 267-286. https://doi.org/10.1007/s10959-008-0146-x

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Access to Document

10.1007/s10959-008-0146-x