Results 11 to 20 of about 3,561,036 (197)

Bayesian Integrated Nested Laplace Approximation (INLA) Longevity Bonds Market Model

open access: yesRisks
Pricing coupon longevity bonds (CLBs) is challenging in illiquid markets due to the incompleteness of insurance markets and the unavailability of longevity payout data.
Yethu Sithole, Samuel Asante Gyamerah
doaj   +3 more sources

Importance Sampling with the Integrated Nested Laplace Approximation [PDF]

open access: yesJournal of Computational and Graphical Statistics, 2021
The integrated nested Laplace approximation (INLA) is a deterministic approach to Bayesian inference on latent Gaussian models (LGMs) and focuses on fast and accurate approximation of posterior marginals for the parameters in the models.
Gómez-Rubio, Virgilio   +4 more
core   +5 more sources

Simplified Integrated Nested Laplace Approximation [PDF]

open access: yesBiometrika, 2019
Integrated nested Laplace approximation provides accurate and efficient approximations for marginal distributions in latent Gaussian random field models. Computational feasibility of the original Rue et al.
Wood, Simon N, Simon N Wood
core   +5 more sources

Animal Models and Integrated Nested Laplace Approximations [PDF]

open access: yesG3 Genes|Genomes|Genetics, 2013
Animal models are generalized linear mixed models used in evolutionary biology and animal breeding to identify the genetic part of traits. Integrated Nested Laplace Approximation (INLA) is a methodology for making fast, nonsampling-based Bayesian ...
Steinsland, Ingelin   +3 more
core   +6 more sources

Integrated nested laplace approximation for bayesian nonparametric phylodynamics [PDF]

open access: yes, 2012
The goal of phylodynamics, an area on the intersection of phylogenetics and population genetics, is to reconstruct population size dynamics from genetic data.
Palacios, JA, Minin, VN
core   +6 more sources

The Integrated Nested Laplace Approximation for fitting Dirichlet regression models [PDF]

open access: yesJournal of Computational and Graphical Statistics, 2022
This paper 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. These data,
Simpson, Daniel   +5 more
core   +4 more sources

Fitting complex ecological point process models with integrated nested Laplace approximation [PDF]

open access: yesMethods in Ecology and Evolution, 2013
Summary 1. We highlight an emerging statistical method, integrated nested Laplace approximation (INLA), which is ideally suited for fitting complex models to many of the rich spatial data sets that ecologists wish to analyse. 2.
Gallego-Fernández, Juan B.   +9 more
core   +5 more sources

A Novel Method of Marginalisation using Low Discrepancy Sequences for Integrated Nested Laplace Approximations [PDF]

open access: yesComputational Statistics & Data Analysis, 2019
Recently, it has been shown that approximations to marginal posterior distributions obtained using a low discrepancy sequence (LDS) can outperform standard grid-based methods with respect to both accuracy and computational efficiency. This recent method,
Joe, Stephen   +3 more
core   +5 more sources

Multivariate Posterior Inference for Spatial Models with the Integrated Nested Laplace Approximation

open access: yesJournal of the Royal Statistical Society Series C: Applied Statistics, 2018
Summary 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
Virgilio Gómez-Rubio   +1 more
core   +3 more sources

Bayesian scanning of spatial disease rates with integrated nested Laplace approximation (INLA)

open access: yesStatistical Methods & Applications, 2014
Among the many tools suited to detect local clusters in group-level data, Kulldorff–Nagarwalla’s spatial scan statistic gained wide popularity (Kulldorff and Nagarwalla in Stat Med 14(8):799–810, 1995).
DEMARINIS G., BILANCIA, Massimo
core   +3 more sources

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