Comparison of predictions by kriging and spatial autoregressive models

DOI10.1080/03610918.2017.1324980OpenAlexW2612372811MaRDI QIDQ5084955

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Publication date: 29 June 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2017.1324980

zbMATH Keywords

predictionkrigingspatial dataspatial autoregressive modelregular lattice

Mathematics Subject Classification ID

Directional data; spatial statistics (62H11) Inference from stochastic processes and prediction (62M20)

Related Items (4)

Impact of missing data on the prediction of random fields ⋮ An optimal prediction in stationary random fields based on a new interpolation approach ⋮ Non-stationary spatial autoregressive modeling for the prediction of lattice data ⋮ Comparison of Kriging and artificial neural network models for the prediction of spatial data

Cites Work

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• Least-modules estimates for spatial autoregression coefficients
• Gaussian maximum likelihood estimation for ARMA models. II: Spatial processes
• The stationary regions for the parameter space of unilateral second-order spatial AR model
• Statistical spatial series modelling II: Some further results on unilateral lattice processes
• Properties of the spatial unilateral first-order ARMA model
• Estimation Methods for Models of Spatial Interaction
• Statistical spatial series modelling
• A subclass of lattice processes applied to a problem in planar sampling
• Physical nearest-neighbour models and non-linear time-series
• Statistics for Spatial Data
• ON STATIONARY PROCESSES IN THE PLANE

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