Results 21 to 30 of about 3,106 (192)
Integrated Nested Laplace Approximations within Monte Carlo Methods [PDF]
, 2020 Integrated Nested Laplace Approximations (INLA) er en deterministisk metode for å oppnå bayesiansk inferens på latente gaussiske modeller (LGMer) og fokuserer på raske og nøyaktige approksimasjoner av marginale posteriori-fordelinger for parametrene i en modell.
Berild, Martin Outzen
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The integrated nested Laplace approximation applied to spatial log-Gaussian Cox process models. [PDF]
J Appl Stat, 2023 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. The log-Gaussian Cox process (LGCP) is a point process driven by a latent Gaussian field, and recent advances have ...
Flagg K, Hoegh A.
europepmc +3 more sources
Bayesian models for missing and misclassified variables using integrated nested Laplace approximations [PDF]
Misclassified variables used in regression models, either as a covariate or as the response, may lead to biased estimators and incorrect inference. Even though Bayesian models to adjust for misclassification error exist, it has not been shown how these models can be implemented using integrated nested Laplace approximation (INLA), a popular framework ...
Skarstein, Emma +3 more
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Fitting double hierarchical models with the integrated nested Laplace approximation
Statistics and Computing, 2022 AbstractDouble hierarchical generalized linear models (DHGLM) are a family of models that are flexible enough as to model hierarchically the mean and scale parameters. In a Bayesian framework, fitting highly parameterized hierarchical models is challenging when this problem is addressed using typical Markov chain Monte Carlo (MCMC) methods due to the ...
Mabel Morales-Otero +2 more
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Estimating the expected value of partial perfect information in health economic evaluations using integrated nested Laplace approximation. [PDF]
Stat Med, 2016 The Expected Value of Perfect Partial Information (EVPPI) is a decision-theoretic measure of the ‘cost’ of parametric uncertainty in decision making used principally in health economic decision making.
Heath A, Manolopoulou I, Baio G.
europepmc +3 more sources
Parallelized integrated nested Laplace approximations for fast Bayesian inference
Statistics and Computing, 2022 There is a growing demand for performing larger-scale Bayesian inference tasks, arising from greater data availability and higher-dimensional model parameter spaces. In this work we present parallelization strategies for the methodology of integrated nested Laplace approximations (INLA), a popular framework for performing approximate Bayesian inference
Lisa Gaedke-Merzhäuser +3 more
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Spatial modelling of agro-ecologically significant grassland species using the INLA-SPDE approach
Scientific Reports, 2023 The use of spatially referenced data in agricultural systems modelling has grown in recent decades, however, the use of spatial modelling techniques in agricultural science is limited.
Andrew Fichera +4 more
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An Introduction to Predictive Processing Models of Perception and Decision‐Making
Topics in Cognitive Science, EarlyView., 2023 Abstract The predictive processing framework includes a broad set of ideas, which might be articulated and developed in a variety of ways, concerning how the brain may leverage predictive models when implementing perception, cognition, decision‐making, and motor control.
Mark Sprevak, Ryan Smith
wiley +1 more source
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). INLA is based on producing an accurate approximation to the posterior marginal distributions of the parameters in the model and some other ...
Virgilio Gómez-Rubio, Håvard Rue
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BMC Public Health, 2022 Background Overweight and obesity are one of the most significant risk factors of the twenty-first century related to an increased risk in the occurrence of non-communicable diseases and associated increased healthcare costs.
Robby De Pauw +5 more
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