Fixed-Domain Posterior Contraction Rates for Spatial Gaussian Process Model with Nugget

Cites Work

Title not available (Why is that?)
Title not available (Why is that?)
A simple condition for asymptotic optimality of linear predictions of random fields
Hanson-Wright inequality and sub-Gaussian concentration
Uniform asymptotic optimality of linear predictions of a random field using an incorrect second-order structure
Asymptotic properties of a maximum likelihood estimator with data from a Gaussian process
Estimating the smoothness of a Gaussian random field from irregularly spaced data via higher-order quadratic variations
Fixed-domain asymptotic properties of tapered maximum likelihood estimators
Asymptotically efficient prediction of a random field with a missspecified covariance function
Interpolation of spatial data. Some theory for kriging
Equivalence and orthogonality of Gaussian measures on spheres
Estimation and prediction using generalized Wendland covariance functions under fixed domain asymptotics
Bounds on the efficiency of linear predictions using an incorrect covariance function
Equivalence of Gaussian measures for some nonstationary random fields
On fixed-domain asymptotics and covariance tapering in Gaussian random field models
Composite likelihood estimation for a Gaussian process under fixed domain asymptotics
On fixed-domain asymptotics, parameter estimation and isotropic Gaussian random fields with Matérn covariance functions
Bayesian fixed-domain asymptotics for covariance parameters in a Gaussian process model
Fixed-domain asymptotic properties of maximum composite likelihood estimators for Gaussian processes
A case study competition among methods for analyzing large spatial data
Fixed-domain asymptotics for a subclass of Matérn-type Gaussian random fields
On the consistent separation of scale and variance for Gaussian random fields
Cross-validation estimation of covariance parameters under fixed-domain asymptotics
Equivalence of measures and asymptotically optimal linear prediction for Gaussian random fields with fractional-order covariance operators
Maximum likelihood estimation of models for residual covariance in spatial regression
Towards reconciling two asymptotic frameworks in spatial statistics
Gaussian Predictive Process Models for Large Spatial Data Sets
Bayesian Prediction of Transformed Gaussian Random Fields
A Full Scale Approximation of Covariance Functions for Large Spatial Data Sets
On Identifiability and Consistency of The Nugget in Gaussian Spatial Process Models
Simple, scalable and accurate posterior interval estimation
The role of the range parameter for estimation and prediction in geostatistics
Covariance Tapering for Likelihood-Based Estimation in Large Spatial Data Sets
Inconsistent Estimation and Asymptotically Equal Interpolations in Model-Based Geostatistics
On Bayes procedures
Fundamentals of Nonparametric Bayesian Inference
Highly Scalable Bayesian Geostatistical Modeling via Meshed Gaussian Processes on Partitioned Domains
Scattered Data Approximation
A general framework for Vecchia approximations of Gaussian processes
Estimating the parameters of some common Gaussian random fields with nugget under fixed-domain asymptotics

This page was built for publication: Fixed-Domain Posterior Contraction Rates for Spatial Gaussian Process Model with Nugget

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6567928)