Results 31 to 40 of about 1,710 (136)
Bayesian Spatial Modelling with R-INLA
Journal of Statistical Software, 2015 The principles behind the interface to continuous domain spatial models in the R- INLA software package for R are described. The integrated nested Laplace approximation (INLA) approach proposed by Rue, Martino, and Chopin (2009) is a computationally ...
Finn Lindgren, Håvard Rue
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Integrated Nested Laplace Approximations (INLA)
, 2019 This is a short description and basic introduction to the Integrated nested Laplace approximations (INLA) approach. INLA is a deterministic paradigm for Bayesian inference in latent Gaussian models (LGMs) introduced in Rue et al. (2009). INLA relies on a combination of analytical approximations and efficient numerical integration schemes to achieve ...
Martino, Sara, Riebler, Andrea
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Estimating the marginal likelihood with Integrated nested Laplace approximation (INLA)
, 2016 The marginal likelihood is a well established model selection criterion in Bayesian statistics. It also allows to efficiently calculate the marginal posterior model probabilities that can be used for Bayesian model averaging of quantities of interest.
Hubin, Aliaksandr, Storvik, Geir
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Forest Ecology and Management, 2020 Abstract A novel methodological framework is presented for climate-sensitive modeling of annual radial stem increments using tree-ring width time series. The approach is based on a hierarchical Bayes model together with a distributed time lag model that take into account the effects of a series of monthly temperature and precipitation values, as well
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Approximate Bayesian inference based on INLA algorithm
Statistical Theory and Related FieldsThe integrated nested Laplace approximation (INLA) algorithm provides a computationally efficient approach for approximate Bayesian inference, overcoming the limitations of traditional Markov chain Monte Carlo (MCMC) methods.
Pingping Wang, Wei Zhao, Yincai Tang
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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 +5 more
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Entropy, 2022 Medical data are often missing during epidemiological surveys and clinical trials. In this paper, we propose the MCMCINLA estimation method to account for missing data.
Jiaqi Teng +4 more
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survHE: Survival Analysis for Health Economic Evaluation and Cost-Effectiveness Modeling
Journal of Statistical Software, 2020 Survival analysis features heavily as an important part of health economic evaluation, an increasingly important component of medical research. In this setting, it is important to estimate the mean time to the survival endpoint using limited information (
Gianluca Baio
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Comparison of inference methods of genetic parameters with an application to body weight in broilers [PDF]
Archives Animal Breeding, 2015 REML (restricted maximum likelihood) has become the standard method of variance component estimation in animal breeding. Inference in Bayesian animal models is typically based upon Markov chain Monte Carlo (MCMC) methods, which are generally flexible but
G. Maniatis +4 more
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Geometric overdispersion facilitates the integration of ecological data
Methods in Ecology and Evolution, EarlyView.Abstract Statistical data integration facilitates inference based on the variety of data prevalent in ecology. In particular, integrated distribution models (IDMs) have been proposed for inferring spatial patterns in abundance using combinations of noisy count, presence–absence and presence–only data.
Justin J. Van Ee +4 more
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