Pages that link to "Item:Q4665845"
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The following pages link to Approximating Likelihoods for Large Spatial Data Sets (Q4665845):
Displaying 50 items.
- Hierarchical sparse Cholesky decomposition with applications to high-dimensional spatio-temporal filtering (Q2114043) (← links)
- Low-rank multi-parametric covariance identification (Q2114111) (← links)
- Partitioned method of valid moment marginal model with Bayes interval estimates for correlated binary data with time-dependent covariates (Q2135930) (← links)
- Airflow recovery from thoracic and abdominal movements using synchrosqueezing transform and locally stationary Gaussian process regression (Q2157494) (← links)
- A scalable Bayesian nonparametric model for large spatio-temporal data (Q2184402) (← links)
- Fixed-domain asymptotic properties of maximum composite likelihood estimators for Gaussian processes (Q2189098) (← links)
- Block-band behavior of spatial correlations: an analytical asymptotic study in a spatial exponential family data setup (Q2237805) (← links)
- Estimating high-resolution red sea surface temperature hotspots, using a low-rank semiparametric spatial model (Q2245130) (← links)
- Anisotropic Matérn correlation and spatial prediction using REML (Q2259647) (← links)
- A case study competition among methods for analyzing large spatial data (Q2272997) (← links)
- Spatial disease mapping using directed acyclic graph auto-regressive (DAGAR) models (Q2290712) (← links)
- Towards a complete picture of stationary covariance functions on spheres cross time (Q2316610) (← links)
- Tucker tensor analysis of Matérn functions in spatial statistics (Q2324355) (← links)
- Spatial composite likelihood inference using local C-vines (Q2350040) (← links)
- Likelihood approximation with hierarchical matrices for large spatial datasets (Q2416774) (← links)
- Stochastic approximation of score functions for Gaussian processes (Q2443174) (← links)
- Matérn-based nonstationary cross-covariance models for global processes (Q2451624) (← links)
- Penalized Whittle likelihood for spatial data (Q2692930) (← links)
- Interpolation of spatial data -- a stochastic or a deterministic problem? (Q2870835) (← links)
- Non-stationary cross-covariance models for multivariate processes on a globe (Q2911695) (← links)
- Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations (with discussion) (Q2920273) (← links)
- Efficient pairwise composite likelihood estimation for spatial-clustered data (Q2927619) (← links)
- Pseudo-Likelihoods for Bayesian Inference (Q2963082) (← links)
- Hierarchical Low Rank Approximation of Likelihoods for Large Spatial Datasets (Q3391136) (← links)
- Scalable Gaussian Process Computations Using Hierarchical Matrices (Q3391422) (← links)
- Fourier Analysis of Irregularly Spaced Data on<i>R</i><i>d</i> (Q3551038) (← links)
- Gaussian Predictive Process Models for Large Spatial Data Sets (Q3631475) (← links)
- Hierarchical Spatial Modeling of Additive and Dominance Genetic Variance for Large Spatial Trial Datasets (Q3636988) (← links)
- Fast Spatial Gaussian Process Maximum Likelihood Estimation via Skeletonization Factorizations (Q4601605) (← links)
- Estimating Space and Space-Time Covariance Functions for Large Data Sets: A Weighted Composite Likelihood Approach (Q4916458) (← links)
- A Resampling-Based Stochastic Approximation Method for Analysis of Large Geostatistical Data (Q4916950) (← links)
- Practical Bayesian modeling and inference for massive spatial data sets on modest computing environments<sup>†</sup> (Q4970245) (← links)
- Sparse Cholesky Factorization by Kullback--Leibler Minimization (Q4997432) (← links)
- On Deconfounding Spatial Confounding in Linear Models (Q5050818) (← links)
- (Q5054610) (← links)
- Making Recursive Bayesian Inference Accessible (Q5056965) (← links)
- Adaptive Design and Analysis Via Partitioning Trees for Emulation of a Complex Computer Code (Q5057264) (← links)
- A Fused Gaussian Process Model for Very Large Spatial Data (Q5065995) (← links)
- An Approach to Incorporate Subsampling Into a Generic Bayesian Hierarchical Model (Q5066475) (← links)
- Gaussian Process Prediction using Design-Based Subsampling (Q5066795) (← links)
- A Vecchia approximation for high-dimensional Gaussian cumulative distribution functions arising from spatial data (Q5086084) (← links)
- Scaled Vecchia Approximation for Fast Computer-Model Emulation (Q5097836) (← links)
- Fine-Scale Spatiotemporal Air Pollution Analysis Using Mobile Monitors on Google Street View Vehicles (Q5120650) (← links)
- Semi-parametric estimation of the variogram scale parameter of a Gaussian process with stationary increments (Q5140346) (← links)
- (Q5149246) (← links)
- Spline-Based Emulators for Radiative Shock Experiments With Measurement Error (Q5327264) (← links)
- Scalable inference for space‐time Gaussian Cox processes (Q5377195) (← links)
- Statistical Methods for Regular Monitoring Data (Q5490613) (← links)
- Inference of a Hidden Spatial Tessellation from Multivariate Data: Application to the Delineation of Homogeneous Regions in an Agricultural Field (Q5757841) (← links)
- Statistical Modeling for Spatio-Temporal Data From Stochastic Convection-Diffusion Processes (Q5881150) (← links)
