Pages that link to "Item:Q4665845"
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The following pages link to Approximating Likelihoods for Large Spatial Data Sets (Q4665845):
Displaying 35 items.
- Highly Scalable Bayesian Geostatistical Modeling via Meshed Gaussian Processes on Partitioned Domains (Q5885120) (← links)
- An adaptive spatial model for precipitation data from multiple satellites over large regions (Q5962747) (← links)
- A general framework for Vecchia approximations of Gaussian processes (Q6032766) (← links)
- Bayesian latent variable co-kriging model in remote sensing for quality flagged observations (Q6050918) (← links)
- Linear-Cost Covariance Functions for Gaussian Random Fields (Q6107197) (← links)
- Distributed Bayesian inference in massive spatial data (Q6111472) (← links)
- Bayesian nonstationary and nonparametric covariance estimation for large spatial data (with discussion) (Q6121621) (← links)
- Bayesian hierarchical modeling and analysis for actigraph data from wearable devices (Q6138608) (← links)
- Fast Bayesian inference of block nearest neighbor Gaussian models for large data (Q6171799) (← links)
- Correlation-based sparse inverse Cholesky factorization for fast Gaussian-process inference (Q6172908) (← links)
- Scalable computations for nonstationary Gaussian processes (Q6173565) (← 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)
- Nearest-neighbor mixture models for non-Gaussian spatial processes (Q6203346) (← links)
- BRISC: bootstrap for rapid inference on spatial covariances (Q6541456) (← links)
- A localized ensemble of approximate Gaussian processes for fast sequential emulation (Q6548820) (← links)
- Nearest neighbors weighted composite likelihood based on pairs for (non-)Gaussian massive spatial data with an application to Tukey-\(hh\) random fields estimation (Q6554236) (← links)
- Scalable Bayesian Transport Maps for High-Dimensional Non-Gaussian Spatial Fields (Q6567936) (← links)
- The Matérn model: a journey through statistics, numerical analysis and machine learning (Q6579154) (← links)
- Likelihood-Free Parameter Estimation with Neural Bayes Estimators (Q6585610) (← links)
- 30 years of space-time covariance functions (Q6602109) (← links)
- Nearest-neighbor sparse Cholesky matrices in spatial statistics (Q6602373) (← links)
- Fixed-domain asymptotics under Vecchia's approximation of spatial process likelihoods (Q6621340) (← links)
- Bayesian spatial models for voxel-wise prostate cancer classification using multi-parametric magnetic resonance imaging data (Q6622252) (← links)
- Permutation and Grouping Methods for Sharpening Gaussian Process Approximations (Q6622448) (← links)
- Meta-Kriging: Scalable Bayesian Modeling and Inference for Massive Spatial Datasets (Q6622449) (← links)
- Nonseparable covariance models on circles cross time: a study of Mexico City ozone (Q6626087) (← links)
- Computationally efficient nonstationary nearest-neighbor Gaussian process models using data-driven techniques (Q6626105) (← links)
- High-dimensional multivariate geostatistics: a Bayesian matrix-normal approach (Q6626391) (← links)
- Recursive nearest neighbor co-kriging models for big multi-fidelity spatial data sets (Q6626668) (← links)
- A Scalable Gaussian Process for Large-Scale Periodic Data (Q6631142) (← links)
- A Randomized Pairwise Likelihood Method for Complex Statistical Inferences (Q6631728) (← links)
- Bayesian nonparametric generative modeling of large multivariate non-Gaussian spatial fields (Q6655987) (← links)
- Implementation and analysis of GPU algorithms for Vecchia approximation (Q6657815) (← links)
- Fast adaptive Fourier integration for spectral densities of Gaussian processes (Q6657828) (← links)
