Results 41 to 50 of about 14,071 (177)
Mathematics, 2021 In this paper, we review overdispersed Bayesian generalized spatial conditional count data models. Their usefulness is illustrated with their application to infant mortality rates from Colombian regions and by comparing them with the widely used Besag ...
Mabel Morales-Otero +1 more
doaj +1 more source
Modeling and Estimation for Self-Exciting Spatio-Temporal Models of Terrorist Activity [PDF]
, 2017 Spatio-temporal hierarchical modeling is an extremely attractive way to model the spread of crime or terrorism data over a given region, especially when the observations are counts and must be modeled discretely.
Clark, Nicholas +2 more
core +4 more sources
Journal of Transportation Safety & Security, 2020 Improving traffic safety is a priority of most transportation agencies around the world. As part of traffic safety management strategies, efforts have focused on developing more accurate crash-frequency models and on identifying contributing factors in ...
Romi Satria +2 more
semanticscholar +1 more source
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
openaire +2 more sources
Spatial Data Analysis with R-INLA with Some Extensions
Journal of Statistical Software, 2015 The integrated nested Laplace approximation (INLA) provides an interesting way of approximating the posterior marginals of a wide range of Bayesian hierarchical models.
Roger Bivand +2 more
doaj +1 more source
Methods in Ecology and Evolution, 2012 Summary1. Spatial analysis of ecological data is central to many interesting questions in ecology. Bayesian implementation of spatially explicit models has received increasing attention from ecologists as Monte Carlo Markov Chain (MCMC) methods have become freely accessible. MCMC simulations offer a flexible framework for modelling extensive ecological
J. Beguin +3 more
semanticscholar +2 more sources
Integrated Nested Laplace Approximation for Bayesian Nonparametric Phylodynamics
, 2012 Appears in Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI2012)
Palacios, JA, Minin, VN
openaire +3 more sources
Rational Krylov for Stieltjes matrix functions: convergence and pole selection
, 2020 Evaluating the action of a matrix function on a vector, that is $x=f(\mathcal M)v$, is an ubiquitous task in applications. When $\mathcal M$ is large, one usually relies on Krylov projection methods.
Massei, Stefano, Robol, Leonardo
core +1 more source
Palm distributions for log Gaussian Cox processes [PDF]
, 2015 This paper establishes a remarkable result regarding Palmdistributions for a log Gaussian Cox process: the reduced Palmdistribution for a log Gaussian Cox process is itself a log Gaussian Coxprocess which only differs from the original log Gaussian Cox ...
Coeurjolly, Jean-François +2 more
core +4 more sources
Journal of the Royal Statistical Society: Series A (Statistics in Society)Spatially misaligned data can be fused by using a Bayesian melding model that assumes that underlying all observations there is a spatially continuous Gaussian random field.
Ruiman Zhong +2 more
semanticscholar +1 more source