Pages that link to "Item:Q4547586"

The following pages link to Spectral methods for nonstationary spatial processes (Q4547586):

Displaying 40 items.

• Inference with the Whittle Likelihood: A Tractable Approach Using Estimating Functions (Q2968464) (← links)
• A Class of Convolution-Based Models for Spatio-Temporal Processes with Non-Separable Covariance Structure (Q3103140) (← links)
• Calibrated spatial moving average simulations (Q3427635) (← links)
• Interpolation of nonstationary air pollution processes: a spatial spectral approach (Q3427636) (← links)
• A kernel-based spectral model for non-Gaussian spatio-temporal processes (Q3427637) (← links)
• A spectral method for spatial downscaling (Q3465371) (← links)
• Aberrant Crypt Foci and Semiparametric Modeling of Correlated Binary Data (Q3506500) (← links)
• Bayesian spatio-temporal models based on discrete convolutions (Q3526429) (← links)
• Covariance functions that are stationary or nonstationary in space and stationary in time (Q3592397) (← links)
• Hierarchical Spatial Modeling of Additive and Dominance Genetic Variance for Large Spatial Trial Datasets (Q3636988) (← links)
• Outlier–robust spectral estimation for spatial lattice processes (Q4246308) (← links)
• Hierarchical Models in Environmental Science (Q4832049) (← links)
• Statistical Assessment of Numerical Models* (Q4832050) (← links)
• Nonstationary Modeling With Sparsity for Spatial Data via the Basis Graphical Lasso (Q5066402) (← links)
• On the estimation of the spectral density for continuous spatial processes (Q5402491) (← links)
• (Q5424579) (← links)
• Geostatistical Analysis Through Spectral Techniques: Some Words of Caution (Q5436421) (← links)
• Model Evaluation and Spatial Interpolation by Bayesian Combination of Observations with Outputs from Numerical Models (Q5715350) (← links)
• Generalized spatial stick-breaking processes (Q5867488) (← links)
• Lagrangian Spatio-Temporal Nonstationary Covariance Functions (Q5871012) (← links)
• An adaptive spatial model for precipitation data from multiple satellites over large regions (Q5962747) (← links)
• Comment on ``Probabilistic integration: a role in statistical computation?'' (Q5971034) (← links)
• Comments on: ``Comparing and selecting spatial predictors using local criteria'' (Q5971084) (← links)
• Constructing valid spatial processes on the sphere using kernel convolutions (Q6069106) (← links)
• Bayesian Spatiotemporal Modeling on Complex-Valued fMri Signals via Kernel Convolutions (Q6079745) (← links)
• Modeling Nonstationarity in Space and Time (Q6079971) (← links)
• Covariate‐based cepstral parameterizations for time‐varying spatial error covariances (Q6090018) (← links)
• Estimation of the Spatial Weighting Matrix for Spatiotemporal Data under the Presence of Structural Breaks (Q6094098) (← links)
• Bayesian nonstationary and nonparametric covariance estimation for large spatial data (with discussion) (Q6121621) (← links)
• Regression‐based covariance functions for nonstationary spatial modeling (Q6139146) (← links)
• Bayesian modeling of discrete-time point-referenced spatio-temporal data (Q6149602) (← links)
• Assessing fit in Bayesian models for spatial processes (Q6179536) (← links)
• A general procedure for selecting a class of fully symmetric space‐time covariance functions (Q6179628) (← links)
• DeepKriging: Spatially Dependent Deep Neural Networks for Spatial Prediction (Q6185130) (← links)
• Space-time covariance models on networks (Q6200886) (← links)
• A comparison of a traditional geostatistical regression approach and a general Gaussian process approach for spatial prediction (Q6537795) (← links)
• A diffusion-based spatio-temporal extension of Gaussian Matérn fields (Q6583113) (← links)
• Mixture of Regression Models for Large Spatial Datasets (Q6621664) (← links)
• Modeling spatial data using local likelihood estimation and a Matérn to spatial autoregressive translation (Q6626172) (← links)
• Estimation of Spatial Deformation for Nonstationary Processes via Variogram Alignment (Q6631915) (← links)