Practically applicable central limit theorem for spatial statistics

DOI10.1007/s11004-008-9184-2zbMath1177.60033OpenAlexW1984646146MaRDI QIDQ1035762

Byeong U. Park, Tae Yoon Kim, Jeong-Soo Park, Sun Young Hwang

Publication date: 4 November 2009

Published in: Mathematical Geosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11004-008-9184-2

zbMATH Keywords

central limit theoremdensity estimationnearly infill domain sampling

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Central limit and other weak theorems (60F05) Geostatistics (86A32)

Related Items (6)

Asymptotic normality of kernel type regression estimators for random fields ⋮ Consistency of the mean and the principal components of spatially distributed functional data ⋮ Dependent functional data ⋮ On nonparametric variogram estimation ⋮ An asymptotic theory for the nugget estimator in spatial models ⋮ Using bimodal kernel for inference in nonparametric regression with correlated errors

Uses Software

• spBayes

Cites Work

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• Limit theorems for the empirical distribution function in the spatial case.
• Theoretical comparisons of block bootstrap methods
• Optimal asymptotic quadratic errors of density estimators on random fields.
• Density estimation under long-range dependence
• On bandwidth choice for density estimation with dependent data
• Approximation Theorems of Mathematical Statistics
• A Proof of the Generalized Second-Limit Theorem in the Theory of Probability

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