Pages that link to "Item:Q5229926"
From MaRDI portal
The following pages link to Constructing Priors that Penalize the Complexity of Gaussian Random Fields (Q5229926):
Displaying 45 items.
- Modeling and simulating depositional sequences using latent Gaussian random fields (Q2040696) (← links)
- Spatiotemporal probabilistic wind vector forecasting over Saudi Arabia (Q2044259) (← links)
- Intuitive joint priors for variance parameters (Q2057345) (← links)
- Bayesian prediction of spatial data with non-ignorable missingness (Q2062380) (← links)
- A non-stationary model for spatially dependent circular response data based on wrapped Gaussian processes (Q2080349) (← links)
- The SPDE approach to Matérn fields: graph representations (Q2092895) (← links)
- A spatial modeling framework for monitoring surveys with different sampling protocols with a case study for bird abundance in Mid-Scandinavia (Q2102978) (← links)
- Modelling sub-daily precipitation extremes with the blended generalised extreme value distribution (Q2102980) (← links)
- Bayesian fixed-domain asymptotics for covariance parameters in a Gaussian process model (Q2112815) (← links)
- Bayesian multiresolution modeling of georeferenced data: an extension of `LatticeKrig' (Q2143023) (← links)
- Approximate Bayesian inference for analysis of spatiotemporal flood frequency data (Q2154186) (← links)
- Probabilistic forecasts of arctic sea ice thickness (Q2163520) (← links)
- Compression of climate simulations with a nonstationary global spatiotemporal SPDE model (Q2194444) (← links)
- PC priors for residual correlation parameters in one-factor mixed models (Q2220301) (← links)
- Additive multivariate Gaussian processes for joint species distribution modeling with heterogeneous data (Q2226688) (← links)
- Combining heterogeneous spatial datasets with process-based spatial fusion models: a unifying framework (Q2242020) (← links)
- A spliced gamma-generalized Pareto model for short-term extreme wind speed probabilistic forecasting (Q2273005) (← links)
- A unified view on Bayesian varying coefficient models (Q2283580) (← links)
- A general theory for preferential sampling in environmental networks (Q2291547) (← links)
- Spatiotemporal wildfire modeling through point processes with moderate and extreme marks (Q2686054) (← links)
- Improving Bayesian Local Spatial Models in Large Datasets (Q5066391) (← links)
- Convergence of Gaussian Process Regression with Estimated Hyper-Parameters and Applications in Bayesian Inverse Problems (Q5139353) (← links)
- Small Area Estimation for Disease Prevalence Mapping (Q6064364) (← links)
- Disciplinary proper orthogonal decomposition and interpolation for the resolution of parameterized multidisciplinary analysis (Q6070094) (← links)
- Gradient boosting with extreme-value theory for wildfire prediction (Q6100555) (← links)
- Joint modeling and prediction of massive spatio-temporal wildfire count and burnt area data with the INLA-SPDE approach (Q6100559) (← links)
- Spatial 3D Matérn priors for fast whole-brain fMRI analysis (Q6117931) (← links)
- High-dimensional modeling of spatial and spatio-temporal conditional extremes using INLA and Gaussian Markov random fields (Q6144814) (← links)
- Intuitive joint priors for Bayesian linear multilevel models: the R2D2M2 prior (Q6170612) (← links)
- Some models are useful, but how do we know which ones? Towards a unified Bayesian model taxonomy (Q6185714) (← links)
- A stochastic locally diffusive model with neural network-based deformations for global sea surface temperature (Q6543845) (← links)
- Covariance–Based Rational Approximations of Fractional SPDEs for Computationally Efficient Bayesian Inference (Q6552525) (← links)
- Bayesian inference with subset simulation in varying dimensions applied to the Karhunen-Loève expansion (Q6554109) (← links)
- An efficient workflow for modelling high-dimensional spatial extremes (Q6581672) (← links)
- Spatial modeling with R-INLA: a review (Q6602213) (← links)
- A simulation study of disaggregation regression for spatial disease mapping (Q6622210) (← links)
- A joint Bayesian space-time model to integrate spatially misaligned air pollution data in R-INLA (Q6626196) (← links)
- Generalization of the power-law rating curve using hydrodynamic theory and Bayesian hierarchical modeling (Q6626431) (← links)
- A spatiotemporal analysis of NO\(_2\) concentrations during the Italian 2020 COVID-19 lockdown (Q6626450) (← links)
- Spatio-temporal downscaling emulator for regional climate models (Q6626621) (← links)
- Spatial regression modeling via the R2D2 framework (Q6626641) (← links)
- District-level estimation of vaccination coverage: discrete vs continuous spatial models (Q6627765) (← links)
- Conditional probability and ratio-based approaches for mapping the coverage of multi-dose vaccines (Q6629410) (← links)
- A flexible generalized Poisson likelihood for spatial counts constructed by renewal theory, motivated by groundwater quality assessment (Q6655997) (← links)
- Impact of jittering on raster- and distance-based geostatistical analyses of DHS data (Q6669995) (← links)
