Results 51 to 60 of about 14,253 (214)
Hyper-g Priors for Generalized Linear Models [PDF]
, 2010 We develop an extension of the classical Zellner's g-prior to generalized linear models. The prior on the hyperparameter g is handled in a flexible way, so that any continuous proper hyperprior f(g) can be used, giving rise to a large class of hyper-g ...
Bové, Daniel Sabanés, Held, Leonhard
core +1 more source
Spatial Data Analysis with R-INLA with Some Extensions
Journal of Statistical Software, 2015 The integrated nested Laplace approximation (INLA) provides an interesting way of approximating the posterior marginals of a wide range of Bayesian hierarchical models.
Roger Bivand +2 more
doaj +1 more source
Integrated Nested Laplace Approximation for Bayesian Nonparametric Phylodynamics
, 2012 Appears in Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI2012)
Palacios, JA, Minin, VN
openaire +3 more sources
Journal of the Royal Statistical Society: Series A (Statistics in Society)Spatially misaligned data can be fused by using a Bayesian melding model that assumes that underlying all observations there is a spatially continuous Gaussian random field.
Ruiman Zhong +2 more
semanticscholar +1 more source
Palm distributions for log Gaussian Cox processes [PDF]
, 2015 This paper establishes a remarkable result regarding Palmdistributions for a log Gaussian Cox process: the reduced Palmdistribution for a log Gaussian Cox process is itself a log Gaussian Coxprocess which only differs from the original log Gaussian Cox ...
Coeurjolly, Jean-François +2 more
core +4 more sources
International journal of high risk behaviors and addiction, 2022 Background: The control, management, and prevention of driving accidents and risky driving are regarded as concerns for numerous countries, according to the World Health Organization.
M. Fayaz +4 more
semanticscholar +1 more source
Integrated nested Laplace approximations for threshold stochastic volatility models [PDF]
Econometrics and StatisticsAbstract The aim is to implement the integrated nested Laplace approximations (INLA), known to be very fast and efficient, for estimating the parameters of the threshold stochastic volatility (TSV) model. INLA replaces Markov chain Monte Carlo (MCMC) simulations with accurate deterministic approximations. Weakly informative proper priors are used, as
P. de Zea Bermudez +3 more
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Using Integrated Nested Laplace Approximations for Modelling Spatial Healthcare Utilization
, 2012 In recent years, spatial and spatio-temporal modeling have become an important area of research in many fields (epidemiology, environmental studies, disease mapping). In this work we propose different spatial models to study hospital recruitment, including some potentially explicative variables.
MUSIO, MONICA +2 more
openaire +4 more sources
Traffic prediction at signalised intersections using Integrated Nested Laplace Approximation
, 2021 A Bayesian approach to predicting traffic flows at signalised intersections is considered using the the INLA framework. INLA is a deterministic, computationally efficient alternative to MCMC for estimating a posterior distribution. It is designed for latent Gaussian models where the parameters follow a joint Gaussian distribution.
Townsend, D., Nel, C.
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Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations [PDF]
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2009 Summary Structured additive regression models are perhaps the most commonly used class of models in statistical applications. It includes, among others, (generalized) linear models, (generalized) additive models, smoothing spline models, state space models, semiparametric regression, spatial and spatiotemporal models, log-Gaussian Cox
Rue, Havard +2 more
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