Bias expansion of spatial statistics and approximation of differenced lattice point counts

DOI10.1007/s12044-011-0024-9zbMath1307.62143OpenAlexW2057618892MaRDI QIDQ353996

Daniel J. Nordman, Soumendra Nath Lahiri

Publication date: 17 July 2013

Published in: Proceedings of the Indian Academy of Sciences. Mathematical Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s12044-011-0024-9

zbMATH Keywords

spatial processesconvex setslattice dataarea approximationsincreasing domaininfill samplingspatial covariance

Mathematics Subject Classification ID

Directional data; spatial statistics (62H11) Inference from spatial processes (62M30) Estimation in multivariate analysis (62H12) Lattices and convex bodies (number-theoretic aspects) (11H06) Lattices and convex bodies in (2) dimensions (aspects of discrete geometry) (52C05)

Cites Work

• On optimal spatial subsample size for variance estimation
• The minimum period of the Ehrhart quasi-polynomial of a rational polytope
• The jackknife and the bootstrap for general stationary observations
• Fixed-domain asymptotics for variograms using subsampling
• Large sample confidence regions based on subsamples under minimal assumptions
• Integer Programming with a Fixed Number of Variables
• Exponential Sums and Lattice Points II
• Nonparametric Estimation of the Moments of a General Statistic Computed from Spatial Data
• On Barvinok's Algorithm for Counting Lattice Points in Fixed Dimension
• Automatic Block-Length Selection for the Dependent Bootstrap
• A Polynomial Time Algorithm for Counting Integral Points in Polyhedra When the Dimension is Fixed
• On blocking rules for the bootstrap with dependent data
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