Results 61 to 70 of about 14,071 (177)

Improving the INLA approach for approximate Bayesian inference for latent Gaussian models

, 2015
We introduce a new copula-based correction for generalized linear mixed models (GLMMs) within the integrated nested Laplace approximation (INLA) approach for approximate Bayesian inference for latent Gaussian models.
Ferkingstad, Egil, Rue, Håvard
core   +1 more source

“Exact” and Approximate Methods for Bayesian Inference: Stochastic Volatility Case Study

Entropy, 2021
We conduct a case study in which we empirically illustrate the performance of different classes of Bayesian inference methods to estimate stochastic volatility models.
Yuliya Shapovalova
doaj   +1 more source

Bayesian joint spatio-temporal analysis of multiple diseases [PDF]

, 2019
In this paper we propose a Bayesian hierarchical spatio-temporal model for the joint analysis of multiple diseases which includes specific and shared spatial and temporal effects.
Fernández-Navarro, Pablo, Gómez-Rubio, Virgilio, López-Abente, Gonzalo, Palmí-Perales, Francisco, Ramis-Prieto, Rebeca   +4 more
core  

Spatial analysis of bluetongue cases and vaccination of Swiss cattle in 2008 and 2009

Geospatial Health, 2011
Bluetongue (BT) is a vector-borne viral disease of ruminants. The infection is widespread globally with major implications for international animal trade and production.
Katriina J. E. Willgert, Birgit Schroedle, Heinzpeter Schwermer   +2 more
doaj   +1 more source

Generalisations of Fisher Matrices

, 2016
Fisher matrices play an important role in experimental design and in data analysis. Their primary role is to make predictions for the inference of model parameters - both their errors and covariances.
Heavens, Alan
core   +2 more sources

Pseudo-Marginal Bayesian Inference for Gaussian Processes [PDF]

, 2014
The main challenges that arise when adopting Gaussian Process priors in probabilistic modeling are how to carry out exact Bayesian inference and how to account for uncertainty on model parameters when making model-based predictions on out-of-sample data.
Filippone, Maurizio, Girolami, Mark
core   +2 more sources

Functional Brain Response to Emotional Muical Stimuli in Depression, Using INLA Approach for Approximate Bayesian Inference

Basic and Clinical Neuroscience, 2021
Introduction: One of the vital skills which has an impact on emotional health and well-being is the regulation of emotions. In recent years, the neural basis of this process has been considered widely.
Parisa Naseri, Hamid Alavi Majd, Seyyed Mohammad Tabatabaei, Naghmeh Khadembashi, Seyed Morteza Najibi, Atiye Nazari   +5 more
doaj  

Network Density of States

, 2019
Spectral analysis connects graph structure to the eigenvalues and eigenvectors of associated matrices. Much of spectral graph theory descends directly from spectral geometry, the study of differentiable manifolds through the spectra of associated ...
Benson, Austin R., Bindel, David, Dong, Kun   +2 more
core   +1 more source

Assessing the survival time of women with breast cancer in Northwestern Ethiopia: using the Bayesian approach

BMC Women's Health
Background Despite the significant weight of difficulty, Ethiopia's survival rate and mortality predictors have not yet been identified. Finding out what influences outpatient breast cancer patients' survival time was the major goal of this study ...
Chalachew Gashu, Aragaw Eshetie Aguade
doaj   +1 more source

Latent Gaussian modeling and INLA: A review with focus on space-time applications [PDF]

, 2016
Bayesian hierarchical models with latent Gaussian layers have proven very flexible in capturing complex stochastic behavior and hierarchical structures in high-dimensional spatial and spatio-temporal data.
Opitz, Thomas
core   +2 more sources