The following pages link to (Q4494196):
Displaying 42 items.
- High-dimensional order-free multivariate spatial disease mapping (Q74216) (← links)
- Diagnosing Glaucoma Progression with Visual Field Data Using a Spatiotemporal Boundary Detection Method (Q97699) (← links)
- Disease mapping models for data with weak spatial dependence or spatial discontinuities (Q829910) (← links)
- Improving the convergence rate in conditional autoregressive models (Q959216) (← links)
- Approximate inference for disease mapping (Q959339) (← links)
- Empirical Bayes and fully Bayes procedures to detect high-risk areas in disease mapping (Q961731) (← links)
- Swinging for the fence in a league where everyone bunts (Q1790381) (← links)
- Assessing the risk of disruption of wind turbine operations in Saudi Arabia using Bayesian spatial extremes (Q2028587) (← links)
- Improved inference for areal unit count data using graph-based optimisation (Q2058788) (← links)
- MSPOCK: alleviating spatial confounding in multivariate disease mapping models (Q2084438) (← links)
- Spatio-temporal modelling of dengue fever patterns in peninsular Malaysia from 2015--2017 (Q2089373) (← links)
- Linking physics and spatial statistics: a new family of Boltzmann-Gibbs random fields (Q2233567) (← links)
- Comments on: ``Modular regression -- a Lego system for building structured additive distributional regression models with tensor product interactions'' (Q2273141) (← links)
- Spatial disease mapping using directed acyclic graph auto-regressive (DAGAR) models (Q2290712) (← links)
- Spatial modeling of trends in crime over time in Philadelphia (Q2291513) (← links)
- Alleviating spatial confounding for areal data problems by displacing the geographical centroids (Q2316977) (← links)
- A spatial–temporal study of dengue in Peninsular Malaysia for the year 2017 in two different space–time model (Q5037053) (← links)
- Bayesian additive regression trees in spatial data analysis with sparse observations (Q5040537) (← links)
- Spatio-Temporal Modelling of Progression of the COVID–19 Pandemic (Q5048322) (← links)
- Spatio-temporal modelling using B-spline for disease mapping: analysis of childhood cancer trends (Q5124851) (← links)
- A spatial random-effects model for interzone flows: commuting in Northern Ireland (Q5126939) (← links)
- Bayesian analysis of spatial data using different variance and neighbourhood structures (Q5222356) (← links)
- Spatially Dependent Multiple Testing Under Model Misspecification, With Application to Detection of Anthropogenic Influence on Extreme Climate Events (Q5229893) (← links)
- Spatio-temporal parse network-based trajectory modeling on the dynamics of criminal justice system (Q5865425) (← links)
- Disease Mapping With Generative Models (Q5868186) (← links)
- Estimating a causal exposure response function with a continuous error-prone exposure: a study of fine particulate matter and all-cause mortality (Q6045975) (← links)
- Discussion of “Statistical disease mapping for heterogeneous neuroimaging studies” (Q6059485) (← links)
- Bayesian spatial quantile modeling applied to the incidence of extreme poverty in Lima-Peru (Q6136278) (← links)
- Identifying boundaries in spatially continuous risk surfaces from spatially aggregated disease count data (Q6138628) (← links)
- Detection of sparse differential dependent functional brain connectivity (Q6189826) (← links)
- Inducing high spatial correlation with randomly edge-weighted neighborhood graphs (Q6203350) (← links)
- Retrospective sampling in MCMC with an application to COM-Poisson regression (Q6537800) (← links)
- Bias correction for nonignorable missing counts of areal HIV new diagnosis (Q6548795) (← links)
- Spatial modeling with R-INLA: a review (Q6602213) (← links)
- A shared-frailty spatial scan statistic model for time-to-event data (Q6625493) (← links)
- Reds: random ensemble deep spatial prediction (Q6626548) (← links)
- Relative rate of change in cognitive score network dynamics via Bayesian hierarchical models reveal spatial patterns of neurodegeneration (Q6627539) (← links)
- Spatial modeling of individual-level infectious disease transmission: tuberculosis data in Manitoba, Canada (Q6627694) (← links)
- District-level estimation of vaccination coverage: discrete vs continuous spatial models (Q6627765) (← links)
- A spatially discrete approximation to log-Gaussian Cox processes for modelling aggregated disease count data (Q6628748) (← links)
- A spatio-temporal model and inference tools for longitudinal count data on multicolor cell growth (Q6636176) (← links)
- Bayesian modeling of spatial ordinal data from health surveys (Q6656323) (← links)
