A note on asymptotic normality of kernel estimation for linear random fields on \(Z^{2}\)
From MaRDI portal
Publication:927262
DOI10.1007/s10959-008-0146-xzbMath1136.62059OpenAlexW2016111498MaRDI QIDQ927262
Hwai-Chung Ho, Xuewen Lu, Tsung-Lin Cheng
Publication date: 4 June 2008
Published in: Journal of Theoretical Probability (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10959-008-0146-x
Random fields; image analysis (62M40) Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Central limit and other weak theorems (60F05)
Related Items (4)
On local linear regression for strongly mixing random fields ⋮ Block Bootstrapping for Kernel Density Estimators under ψ-Weak Dependence ⋮ On the asymptotic normality of kernel density estimators for causal linear random fields ⋮ Stationary bootstrap for kernel density estimators under \(\psi\)-weak dependence
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Kernel density estimation on random fields
- Some mixing properties of time series models
- Nearest neighbor estimators for random fields
- On central and non-central limit theorems in density estimation for sequences of long-range dependence
- Central limit theorem for the empirical process of a linear sequence with long memory
- Mixing: Properties and examples
- Limit theorems for functionals of moving averages
- Asymptotic normality for non-linear functionals of non-causal linear processes with summable weights
- On the asymptotic expansion of the empirical process of long-memory moving averages
- Asymptotics of weighted empirical processes of linear fields with long-range dependence
- Remarks on Some Nonparametric Estimates of a Density Function
- NONPARAMETRIC ESTIMATORS FOR TIME SERIES
- Conditions for linear processes to be strong-mixing
- On Estimation of a Probability Density Function and Mode
- Kernel density estimation for linear processes
This page was built for publication: A note on asymptotic normality of kernel estimation for linear random fields on \(Z^{2}\)
