Maximum likelihood estimation under a spatial sampling scheme

DOI10.1214/aos/1069362309zbMath0896.62029OpenAlexW1992107402MaRDI QIDQ1354519

Aad W. van der Vaart

Publication date: 6 October 1998

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/aos/1069362309

zbMATH Keywords

asymptotic efficiencylocal asymptotic normalitymaximum likelihood estimator

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Random fields (60G60) Inference from spatial processes (62M30)

Related Items (12)

Fixed-domain asymptotics for a subclass of Matérn-type Gaussian random fields ⋮ Asymptotic analysis of the role of spatial sampling for covariance parameter estimation of Gaussian processes ⋮ Profile Hellinger distance estimation ⋮ Local asymptotic mixed normality of transformed Gaussian models for random fields ⋮ Cross-validation estimation of covariance parameters under fixed-domain asymptotics ⋮ Asymptotic properties of the maximum likelihood and cross validation estimators for transformed Gaussian processes ⋮ Optimal experimental design and some related control problems ⋮ Comment on identification and estimation of nonlinear models using two samples with nonclassical measurement errors ⋮ Composite likelihood estimation for a Gaussian process under fixed domain asymptotics ⋮ Identification and estimation of nonlinear models using two samples with nonclassical measurement errors ⋮ Estimating structured correlation matrices in smooth Gaussian random field models. ⋮ Asymptotic Analysis of Maximum Likelihood Estimation of Covariance Parameters for Gaussian Processes: An Introduction with Proofs

This page was built for publication: Maximum likelihood estimation under a spatial sampling scheme