Approximate Gibbs sampler for efficient inference of hierarchical Bayesian models for grouped count data-Reference-Cited by-同舟云学术

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Approximate Gibbs sampler for efficient inference of hierarchical Bayesian models for grouped count data

Published:2024-07 Issue: Volume: Page:1-20
ISSN:0094-9655
Container-title:Journal of Statistical Computation and Simulation
language:en
Short-container-title:Journal of Statistical Computation and Simulation

Author:

Yü Jin-Zhu¹²^ORCID,Baroud Hiba³⁴

Affiliation:

1. Department of Civil Engineering, University of Texas at Arlington, Arlington, TX, USA

2. Department of Industrial, Manufacturing, and Systems Engineering, University of Texas at Arlington, Arlington, TX, USA

3. Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, TN, USA

4. Department of Computer Science, Vanderbilt University, Nashville, TN, USA

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/00949655.2024.2364843

Reference48 articles.

1. Sequential Bayesian Analysis of Multivariate Count Data

2. Bayesian analysis of a time series of counts with covariates: an application to the control of an infectious disease

3. Hierarchical Poisson models for spatial count data

4. Estimating the spatial distribution of power outages during hurricanes in the Gulf coast region

5. A hierarchical Bayesian approach for assessing infrastructure networks serviceability under uncertainty: A case study of water distribution systems

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