Copertina

A Bayesian hierarchical model for disease mapping that accounts for scaling and heavy-tailed latent effects

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Michal, Victoire, Freitas, Laís Picinini, Schmidt, Alexandra M., Cruz, Oswaldo Gonçalves
Natura:	Preprint
Pubblicazione:	2021
Soggetti:	Methodology
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

A spatio-temporal model to detect potential outliers in disease mapping
di: Michal, Victoire, et al.
Pubblicazione: (2024)

Opaque prior distributions in Bayesian latent variable models
di: Merkle, Edgar C., et al.
Pubblicazione: (2023)

Scalable skewed Bayesian inference for latent Gaussian models
di: Dutta, Shourya, et al.
Pubblicazione: (2025)

Treatment effect estimation under covariate-adaptive randomization with heavy-tailed outcomes
di: Li, Hongzi, et al.
Pubblicazione: (2024)

Scalable Bayesian computation for crossed and nested hierarchical models
di: Papaspiliopoulos, Omiros, et al.
Pubblicazione: (2021)

Markov switching zero-inflated space-time multinomial models for comparing multiple infectious diseases
di: Douwes-Schultz, Dirk, et al.
Pubblicazione: (2024)

Variational inference for hierarchical models with conditional scale and skewness corrections
di: Kock, Lucas, et al.
Pubblicazione: (2025)

Modeling and estimating skewed and heavy-tailed populations via unsupervised mixture models
di: Bee, Marco, et al.
Pubblicazione: (2025)

Robust heavy-tailed versions of generalized linear models with applications in actuarial science
di: Gagnon, Philippe, et al.
Pubblicazione: (2023)

A new class of composite GBII regression models with varying threshold for modelling heavy-tailed data
di: Li, Zhengxiao, et al.
Pubblicazione: (2022)

Bayesian hierarchical models with calibrated mixtures of g-priors for assessing treatment effect moderation in meta-analysis
di: Wang, Qiao, et al.
Pubblicazione: (2024)

Modelling heavy tail data with bayesian nonparametric mixtures
di: Nieto-Barajas, Luis E.
Pubblicazione: (2026)

Bayesian inference for scale mixtures of skew-normal linear models under the centered parameterization
di: de Freitas, João Victor B., et al.
Pubblicazione: (2024)

Joint model with latent disease age: overcoming the need for reference time
di: Ortholand, Juliette, et al.
Pubblicazione: (2024)

A Bayesian joint longitudinal-survival model with a latent stochastic process for intensive longitudinal data
di: Abbott, Madeline R., et al.
Pubblicazione: (2024)

A multiscale Bayesian nonparametric framework for partial hierarchical clustering
di: Schiavon, Lorenzo, et al.
Pubblicazione: (2024)

Calibrating hierarchical Bayesian domain inference for a proportion
di: Lei, Rayleigh, et al.
Pubblicazione: (2025)

Modelling longitudinal polytomous animal data using Bayesian hierarchical models
di: Salvador, Maria Letícia, et al.
Pubblicazione: (2025)

Bayesian Analysis of Sigmoidal Gaussian Cox Processes via Data Augmentation
di: Alie, Renaud, et al.
Pubblicazione: (2022)

Spatial scale-aware tail dependence modeling for high-dimensional spatial extremes
di: Shi, Muyang, et al.
Pubblicazione: (2024)

Robust Bayesian hierarchical models for basket trials enabling joint evaluation of toxicity and efficacy
di: Cao, Zhi, et al.
Pubblicazione: (2025)

Bayesian nonparametric modeling of latent partitions via Stirling-gamma priors
di: Zito, Alessandro, et al.
Pubblicazione: (2023)

Bayesian analysis of nonlinear structured latent factor models using a Gaussian Process Prior
di: Zhang, Yimang, et al.
Pubblicazione: (2025)

Independent Approximates provide a maximum likelihood estimate for heavy-tailed distributions
di: AL-Najafi, Amenah, et al.
Pubblicazione: (2024)

Semi-Implicit Approaches for Large-Scale Bayesian Spatial Interpolation
di: Garneau, Sébastien, et al.
Pubblicazione: (2025)

A novel reference prior for Gaussian hierarchical models with intrinsic conditional autoregressive random effects
di: Ferreira, Marco A. R.
Pubblicazione: (2026)

Causal discovery in heavy-tailed linear structural equation models via scalings
di: Krali, Mario
Pubblicazione: (2025)

On the PM2.5 -- Mortality Association: A Bayesian Model for Spatio-Temporal Confounding
di: Zaccardi, Carlo, et al.
Pubblicazione: (2024)

Gibbs sampling for Bayesian P-splines
di: Gressani, Oswaldo, et al.
Pubblicazione: (2024)

On the universal calibration of heavy-tailed combination tests
di: Chakraborty, Parijat, et al.
Pubblicazione: (2025)

Uncovering latent territorial structure in ICFES Saber 11 performance with Bayesian multilevel spatial models
di: Pardo, Laura, et al.
Pubblicazione: (2025)

Bayesian clustering of high-dimensional data via latent repulsive mixtures
di: Ghilotti, Lorenzo, et al.
Pubblicazione: (2023)

Estimating the proportion of modern contraceptives supplied by the public and private sectors using a Bayesian hierarchical penalized spline model
di: Comiskey, Hannah, et al.
Pubblicazione: (2022)

Learning discrete Bayesian networks with hierarchical Dirichlet shrinkage
di: Dombowsky, Alexander, et al.
Pubblicazione: (2025)

A Low-Rank Bayesian Approach for Geoadditive Modeling
di: Sumalinab, Bryan, et al.
Pubblicazione: (2024)

Heterogeneous readmission prediction with hierarchical effect decomposition and regularization
di: Jiang, Ziren, et al.
Pubblicazione: (2026)

Non-parametric estimation of conditional quantiles for time series with heavy tails
di: Mathew, Deemat C, et al.
Pubblicazione: (2024)

A unifying modelling approach for hierarchical distributed lag models
di: Economou, Theo, et al.
Pubblicazione: (2024)

Unveiling land use dynamics: Insights from a hierarchical Bayesian spatio-temporal modelling of Compositional Data
di: Figueira, Mario, et al.
Pubblicazione: (2024)

Fractional lower-order covariance-based measures for cyclostationary time series with heavy-tailed distributions: application to dependence testing and model order identification
di: Żuławiński, Wojciech, et al.
Pubblicazione: (2026)