The following pages link to spBayes (Q22128):
Displaying 50 items.
- Mitigating unobserved spatial confounding when estimating the effect of supermarket access on cardiovascular disease deaths (Q2078796) (← links)
- A non-stationary model for spatially dependent circular response data based on wrapped Gaussian processes (Q2080349) (← links)
- Accounting for survey design in Bayesian disaggregation of survey-based areal estimates of proportions: an application to the American Community Survey (Q2080736) (← links)
- Mapping interstellar dust with Gaussian processes (Q2080783) (← links)
- A spatial randomness test based on the box-counting dimension (Q2081048) (← links)
- Modeling crop phenology in the US corn belt using spatially referenced SMOS satellite data (Q2084391) (← links)
- Spatially varying coefficient models with sign preservation of the coefficient functions (Q2084430) (← links)
- MSPOCK: alleviating spatial confounding in multivariate disease mapping models (Q2084438) (← links)
- Modeling obesity rate with spatial auto-correlation: a case study (Q2088540) (← links)
- The SPDE approach to Matérn fields: graph representations (Q2092895) (← links)
- Contagion effects of UK small business failures: a spatial hierarchical autoregressive model for binary data (Q2098076) (← links)
- A spatiotemporal analytical outlook of the exposure to air pollution and COVID-19 mortality in the USA (Q2102958) (← links)
- Multi-scale Vecchia approximations of Gaussian processes (Q2102959) (← links)
- Spatial modeling of day-within-year temperature time series: an examination of daily maximum temperatures in Aragón, Spain (Q2102967) (← links)
- A spatial modeling framework for monitoring surveys with different sampling protocols with a case study for bird abundance in Mid-Scandinavia (Q2102978) (← links)
- Bayesian finite-population inference with spatially correlated measurements (Q2103271) (← links)
- A spatial skew-Gaussian process with a specified covariance function (Q2107581) (← links)
- Hierarchical sparse Cholesky decomposition with applications to high-dimensional spatio-temporal filtering (Q2114043) (← links)
- Empirical likelihood for nonparametric regression models with spatial autoregressive errors (Q2131999) (← links)
- Bayesian nonparametric multivariate spatial mixture mixed effects models with application to American Community Survey special tabulations (Q2135345) (← links)
- Multivariate mixed membership modeling: inferring domain-specific risk profiles (Q2135361) (← links)
- Bayesian hierarchical modeling: application towards production results in the Eagle Ford Shale of South Texas (Q2135585) (← links)
- Limitations and performance of three approaches to Bayesian inference for Gaussian copula regression models of discrete data (Q2135899) (← links)
- Dependent Bayesian nonparametric modeling of compositional data using random Bernstein polynomials (Q2137796) (← links)
- Spatial generalized linear models with non-Gaussian translation processes (Q2163485) (← links)
- A directionally varying change points model for quantifying the impact of a point source (Q2163488) (← links)
- On hierarchical Bayesian spatial small area model for binary data under spatial misalignment (Q2172523) (← links)
- A Bayesian approach to disease clustering using restricted Chinese restaurant processes (Q2180068) (← links)
- Multivariate spatial autoregressive model for large scale social networks (Q2182147) (← links)
- Interpolation of daily rainfall data using censored Bayesian spatially varying model (Q2184400) (← links)
- Non-linear failure rate: a Bayes study using Hamiltonian Monte Carlo simulation (Q2191253) (← links)
- Multivariate transformed Gaussian processes (Q2195526) (← links)
- Small area estimation of general parameters: Bayesian transformed spatial prediction approach (Q2195528) (← links)
- Intensity estimation of spatial point processes based on area-aggregated data (Q2195547) (← links)
- Testing normality of data on a multivariate grid (Q2196122) (← links)
- Spatial Bayesian models of tree density with zero inflation and autocorrelation (Q2197340) (← links)
- A nonstationary spatial covariance model for processes driven by point sources (Q2209876) (← links)
- Additive multivariate Gaussian processes for joint species distribution modeling with heterogeneous data (Q2226688) (← links)
- Network vector autoregression with individual effects (Q2230661) (← links)
- Fluctuations of the magnetization in the \(p\)-spin Curie-Weiss model (Q2231657) (← links)
- Spatial distributed lag data fusion for estimating ambient air pollution (Q2233175) (← links)
- Combining heterogeneous spatial datasets with process-based spatial fusion models: a unifying framework (Q2242020) (← links)
- Fast and scalable computations for Gaussian hierarchical models with intrinsic conditional autoregressive spatial random effects (Q2242039) (← links)
- A multivariate spatiotemporal change-point model of opioid overdose deaths in Ohio (Q2247478) (← links)
- Gaussian processes on the support of cylindrical surfaces, with application to periodic spatio-temporal data (Q2250694) (← links)
- Spatio-temporal modelling of extreme storms (Q2258573) (← links)
- Spatial stochastic volatility for lattice data (Q2259630) (← links)
- Spatial designs and properties of spatial correlation: effects on covariance estimation (Q2259829) (← links)
- A statistical framework to combine multivariate spatial data and physical models for hurricane surface wind prediction (Q2259845) (← links)
- Bayesian multivariate process modeling for prediction of forest attributes (Q2259847) (← links)
