Information loss due to incomplete data from a spatial gaussian one-parameter first-order conditional process

DOI10.1080/03610928908830179zbMath0707.62182OpenAlexW2030161792MaRDI QIDQ3489225

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Publication date: 1989

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610928908830179

zbMATH Keywords

correlationspatial processmissing values

Mathematics Subject Classification ID

Non-Markovian processes: estimation (62M09) Point estimation (62F10)

Related Items (6)

Information loss on the dependence parameter due to incomplete data from a one-parameter spatial gaussian process ⋮ Estimation and smoothing from incomplete data for a class of lattice processes ⋮ Application of em-type algorithms to spatial data ⋮ Stochastic complexity and model selection from incomplete data ⋮ Information loss on the mean for spatial processes when some values are missing ⋮ Leverage, influence and residuals in regression models when observations are correlated

Cites Work

• Maximum likelihood estimation of models for residual covariance in spatial regression
• Exact maximum likelihood for incomplete data from a correlated gaussian process
• Efficiency of pseudolikelihood estimation for simple Gaussian fields
• On the estimation and testing of spatial interaction in Gaussian lattice processes

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