Results 81 to 90 of about 14,253 (214)
Bayesian Analysis of Measurement Error Models Using Integrated Nested Laplace Approximations
Journal of the Royal Statistical Society Series C: Applied Statistics, 2014 SummaryTo account for measurement error (ME) in explanatory variables, Bayesian approaches provide a flexible framework, as expert knowledge can be incorporated in the prior distributions. Recently, integrated nested Laplace approximations have been proven to be a computationally convenient alternative to sampling approaches for Bayesian inference in ...
Muff, Stefanie +4 more
openaire +1 more source
Fish and Fisheries, EarlyView.ABSTRACT Rapid changes in marine ecosystems highlight the need to account for time‐varying productivity in stock assessments used to support fisheries management. Common approaches incorporate annual variation or regressing processes such as recruitment, natural mortality, or growth on environmental variables.
J. Champagnat +6 more
wiley +1 more source
Pseudo-Marginal Bayesian Inference for Gaussian Processes [PDF]
, 2014 The main challenges that arise when adopting Gaussian Process priors in probabilistic modeling are how to carry out exact Bayesian inference and how to account for uncertainty on model parameters when making model-based predictions on out-of-sample data.
Filippone, Maurizio, Girolami, Mark
core +2 more sources
Bayesian Nonparametric Regression and Density Estimation Using Integrated Nested Laplace Approximations [PDF]
Journal of Biometrics & Biostatistics, 2013 Integrated nested Laplace approximations (INLA) are a recently proposed approximate Bayesian approach to fit structured additive regression models with latent Gaussian field. INLA method, as an alternative to Markov chain Monte Carlo techniques, provides accurate approximations to estimate posterior marginals and avoid time-consuming sampling.
openaire +2 more sources
International Statistical Review, EarlyView.Summary Understanding the spread of infectious diseases such as COVID‐19 is crucial for informed decision‐making and resource allocation. A critical component of disease behaviour is the velocity with which disease spreads, defined as the rate of change between time and space.
Fernando Rodriguez Avellaneda +2 more
wiley +1 more source
, 2019 Spectral analysis connects graph structure to the eigenvalues and eigenvectors of associated matrices. Much of spectral graph theory descends directly from spectral geometry, the study of differentiable manifolds through the spectra of associated ...
Benson, Austin R. +2 more
core +1 more source
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
doaj +1 more source
Integrated Nested Laplace Approximations for Large-Scale Spatial-Temporal Bayesian Modeling
, 2023 Bayesian inference tasks continue to pose a computational challenge. This especially holds for spatial-temporal modeling where high-dimensional latent parameter spaces are ubiquitous. The methodology of integrated nested Laplace approximations (INLA) provides a framework for performing Bayesian inference applicable to a large subclass of additive ...
Gaedke-Merzhäuser, Lisa +4 more
openaire +2 more sources
Bias Adjustment for Mean Squared Error Estimation in M‐Quantile Models for Small Area Estimation
International Statistical Review, EarlyView.Summary M‐quantile (MQ) regression provides a robust and flexible alternative to mixed models for small area estimation. However, several theoretical aspects remain underexplored. In this paper, a parametric bootstrap method is proposed to approximate the distributions of area‐specific MQ coefficients and applied to adjust the bias in the mean squared ...
María Bugallo +3 more
wiley +1 more source
Econometrics at the Extreme: From Quantile Regression to QFAVAR1
Journal of Economic Surveys, EarlyView.ABSTRACT This paper surveys quantile modelling from its theoretical origins to current advances. We organize the literature and present core econometric formulations and estimation methods for: (i) cross‐sectional quantile regression; (ii) quantile time series models and their time series properties; (iii) quantile vector autoregressions for ...
Stéphane Goutte +4 more
wiley +1 more source