Kernel regression estimation for continuous spatial processes
DOI10.3103/S1066530707040023zbMath1140.62071OpenAlexW2062887393MaRDI QIDQ926975
Anne-Françoise Yao, Sophie Dabo-Niang
Publication date: 21 May 2008
Published in: Mathematical Methods of Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.3103/s1066530707040023
kernel density estimationspatial predictionoptimal rate of convergencespatial processkernel regression estimation
Inference from spatial processes (62M30) Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20)
Related Items (30)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Texture synthesis and nonparametric resampling of random fields
- Resampling methods for spatial regression models under a class of stochastic designs
- Kernel regression estimation for random fields
- Kernel density estimation on random fields
- Kernel regression estimation for continuous spatial processes
- Nonparameteric estimation in mixing sequences of random variables
- Nonparametric function estimation involving time series
- Nearest neighbor estimators for random fields
- Asymptotic normality for density kernel estimators in discrete and continuous time
- Mixing: Properties and examples
- Nonparametric resampling for homogeneous strong mixing random fields
- Parametric rates of nonparametric estimators and predictors for continuous time processes
- Density estimation for a class of continuous time processes
- Distribution-free strong consistency for nonparametric kernel regression involving nonlinear time series
- Kernel density estimation for random fields. (Density estimation for random fields)
- Kernel density estimation for spatial processes: The \(L_{1}\) theory
- On the sharp Markov property for Gaussian random fields and spectral synthesis in spaces of Bessel potentials
- Spatial nonparametric regression estimation: Non-isotropic case
- Kernel density estimator in an infinite-dimensional space with a rate of convergence in the case of diffusion process.
- Spatial kernel regression estimation: weak consistency
- Nonparametric spatial prediction
- A Markov property for set-indexed processes
- Kernel regression estimation when the regressor takes values in metric space
- New directions in spatial econometrics
- Local linear spatial regression
- Nonparametric functional data analysis. Theory and practice.
- Frequency poligons for random fields.
- Nonparametric Estimation and Identification of Nonlinear ARCH Time Series Strong Convergence and Asymptotic Normality: Strong Convergence and Asymptotic Normality
- Kernel density estimation for random fields: TheL1Theory
- Gauss-Markov random fields (CMrf) with continuous indices
- Optimal sampling for density estimation in continuous time
- A family of minimax rates for density estimators in continuous time
- NEAREST‐NEIGHBOUR METHODS FOR TIME SERIES ANALYSIS
- Brownian Motion with a Several-Dimensional Time
This page was built for publication: Kernel regression estimation for continuous spatial processes