Results 11 to 20 of about 21,991 (210)

Spatio‐temporal occupancy models with INLA

Methods in Ecology and Evolution
Modern methods for quantifying, predicting and mapping species distributions have played a crucial part in biodiversity conservation. Occupancy models have become a popular choice for analysing species occurrence data due to their ability to separate out
Jafet Belmont, Sara Martino, Janine Illian, Håvard Rue   +3 more
doaj   +6 more sources

Bayesian Spatial Modelling with R-INLA [PDF]

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   +5 more sources

Bayesian survival analysis with INLA [PDF]

Statistics in Medicine, 2022
This tutorial shows how various Bayesian survival models can be fitted using the integrated nested Laplace approximation in a clear, legible, and comprehensible manner using the INLA and INLAjoint R‐packages. Such models include accelerated failure time,
D. Alvares, J. van Niekerk, E. Krainski, Håvard Rue, Denis Rustand   +4 more
semanticscholar   +6 more sources

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, Rachel King, Jarrod Kath, David Cobon, Kathryn Reardon-Smith   +4 more
doaj   +2 more sources

Bayesian Computing with INLA: A Review [PDF]

Annual Review of Statistics and Its Application, 2016
The key operation in Bayesian inference is to compute high-dimensional integrals. An old approximate technique is the Laplace method or approximation, which dates back to Pierre-Simon Laplace (1774).
H. Rue, A. Riebler, S. H. Sørbye, J. Illian, Daniel P. Simpson, F. Lindgren   +5 more
semanticscholar   +6 more sources

An efficient PG-INLA algorithm for the Bayesian inference of logistic item response models

Statistical Theory and Related Fields
In this paper, we propose a Bayesian PG-INLA algorithm which is tailored to both one-dimensional and multidimensional 2-PL IRT models. The proposed PG-INLA algorithm utilizes a computationally efficient data augmentation strategy via the Pólya-Gamma ...
Xiaofan Lin, Yincai Tang
doaj   +2 more sources

Unveiling the Mutations and Conservation of InlA in Listeria monocytogenes

Microorganisms
Listeria monocytogenes (L. monocytogenes) is a pathogen that is transmitted through contaminated food and causes the illness known as listeriosis. The virulence factor InlA plays a crucial role in the invasion of L.
Lingling Li, Yan Wang, Ji Pu, Jinni Chen, Lingyun Liu, Pan Mao, Hui Sun, Xia Luo, Changyun Ye   +8 more
doaj   +2 more sources

Exploring the usefulness of the INLA model in predicting levels of crime in the City of Johannesburg, South Africa

Crime Science
Crime prediction serves as a valuable tool for deriving insightful information that can inform policy decisions at both operational and strategic tiers.
Toshka Coleman, Paul Mokilane, Mapitsi Rangata, Jenny Holloway, Nicolene Botha, Renee Koen, Nontembeko Dudeni-Tlhone   +6 more
doaj   +2 more sources

A Gibbs-INLA algorithm for multidimensional graded response model analysis.

British Journal of Mathematical and Statistical Psychology, 2023
In this paper, we propose a novel Gibbs-INLA algorithm for the Bayesian inference of graded response models with ordinal response based on multidimensional item response theory. With the combination of the Gibbs sampling and the integrated nested Laplace
Xiaofan Lin, Siliang Zhang, Yincai Tang, Xuan Li   +3 more
semanticscholar   +3 more sources

INLA+\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^+$$\end{document}: approximate Bayesian inference for non-sparse

Statistics and Computing
The integrated nested Laplace approximations (INLA) method has become a widely utilized tool for researchers and practitioners seeking to perform approximate Bayesian inference across various fields of application. To address the growing demand for incorporating more complex models and enhancing the method's capabilities, this paper introduces a novel ...
Esmail Abdul Fattah, J. van Niekerk, Håvard Rue   +2 more
semanticscholar   +4 more sources