The integrated nested Laplace approximation applied to spatial log-Gaussian Cox process models [PDF]
Journal of Applied Statistics, 2022 Spatial point process models are theoretically useful for mapping discrete events, such as plant or animal presence, across space; however, the computational complexity of fitting these models is often a barrier to their practical use.
Kenneth Flagg, A. Hoegh
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Markov chain Monte Carlo with the Integrated Nested Laplace Approximation [PDF]
Statistics and Computing, 2017 The Integrated Nested Laplace Approximation (INLA) has established itself as a widely used method for approximate inference on Bayesian hierarchical models which can be represented as a latent Gaussian model (LGM).
V. Gómez‐Rubio, H. Rue
semanticscholar +6 more sources
Fitting double hierarchical models with the integrated nested Laplace approximation [PDF]
Statistics and Computing, 2022 Double hierarchical generalized linear models (DHGLM) are a family of models that are flexible enough as to model hierarchically the mean and scale parameters.
M. Morales-Otero +2 more
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The Integrated Nested Laplace Approximation for Fitting Dirichlet Regression Models [PDF]
Journal of Computational and Graphical Statistics, 2019 This article introduces a Laplace approximation to Bayesian inference in Dirichlet regression models, which can be used to analyze a set of variables on a simplex exhibiting skewness and heteroscedasticity, without having to transform the data.
J. Martínez-Minaya +4 more
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Spatial Bayesian Hierarchical Modelling with Integrated Nested Laplace Approximation
, 2020 We consider latent Gaussian fields for modelling spatial dependence in the context of both spatial point patterns and areal data, providing two different applications. The inhomogeneous Log-Gaussian Cox Process model is specified to describe a seismic sequence occurred in Greece, resorting to the Stochastic Partial Differential Equations.
D'Angelo, Nicoletta +2 more
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Reparametrization-based estimation of genetic parameters in multi-trait animal model using Integrated Nested Laplace Approximation [PDF]
Theor Appl Genet, 2015 Key messageA novel reparametrization-based INLA approach as a fast alternative to MCMC for the Bayesian estimation of genetic parameters in multivariate animal model is presented.Abstract Multi-trait genetic parameter estimation is a relevant topic in ...
Boby Mathew +4 more
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Multivariate posterior inference for spatial models with the integrated nested Laplace approximation
Journal of the Royal Statistical Society Series C: Applied Statistics, 2018 The integrated nested Laplace approximation (INLA) is a convenient way to obtain approximations to the posterior marginals for parameters in Bayesian hierarchical models when the latent effects can be expressed as a Gaussian Markov random field.
V. Gómez‐Rubio, F. Palmí-Perales
semanticscholar +3 more sources
Bayesian spatio-temporal modeling for policy evaluation: Sensitivity of policy effect estimates in the context of COVID-19 stay-at-home orders. [PDF]
PLoS ONEThis study applies a Bayesian spatio-temporal model to demonstrate the sensitivity of policy effect estimates to spatial and temporal structure, using COVID-19 stay-at-home orders as a case study.
Pyung Kim +3 more
doaj +2 more sources
An Approximate Bayesian Inference for Beta Regression Models [PDF]
Journal of Sciences, Islamic Republic of Iran, 2022 In modeling the variables related to each other, regression models are usually used assuming that the response variable is Normal. But in problems dealing with data such as the rate or ratio of an event distributed in the (0,1) interval, these models may
kobra Gholizadeh Gazvar +1 more
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Validating a Bayesian Spatio-Temporal Model to Predict La Crosse Virus Human Incidence in the Appalachian Mountain Region, USA [PDF]
MicroorganismsLa Crosse virus (LACV) is a rare cause of pediatric encephalitis, yet identifying and mitigating transmission foci is critical to detecting additional cases.
Maggie McCarter +6 more
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