Results 51 to 60 of about 5,528 (174)
Improving the INLA approach for approximate Bayesian inference for latent Gaussian models
, 2015 We introduce a new copula-based correction for generalized linear mixed models (GLMMs) within the integrated nested Laplace approximation (INLA) approach for approximate Bayesian inference for latent Gaussian models.
Ferkingstad, Egil, Rue, Håvard
core +1 more source
Impact of Pneumococcal Conjugate Vaccines on Pneumonia Hospitalizations in High- and Low-Income Subpopulations in Brazil. [PDF]
, 2017 BackgroundPneumococcal conjugate vaccines (PCVs) are being used worldwide. A key question is whether the impact of PCVs on pneumonia is similar in low- and high-income populations.
Kürüm, Esra +7 more
core +2 more sources
Spatial modelling with R-INLA: A review
, 2018 Coming up with Bayesian models for spatial data is easy, but performing inference with them can be challenging. Writing fast inference code for a complex spatial model with realistically-sized datasets from scratch is time-consuming, and if changes are made to the model, there is little guarantee that the code performs well.
Bakka, Haakon +7 more
openaire +2 more sources
New opportunities for grassland species in warming temperate winters
Functional Ecology, EarlyView.Read the free Plain Language Summary for this article on the Journal blog. Abstract Temperate winters are getting warmer, the length of the growing season is increasing and mid‐winter fluctuations of warm and freezing temperatures are more frequent. Although typically winter dormant, some herbaceous perennials can maintain or grow green leaves during ...
F. Curtis Lubbe +3 more
wiley +1 more source
Revista Latinoamericana de Población, 2019 El trabajo busca modelar la distribución de la tasa de incidencia acumulada de COVID-19 en los municipios de México a través del ajuste de tres modelos lineales generalizados (en competencia) con efectos espaciales y temporales y función de enlace ...
Gerardo Núñez Medina
doaj +1 more source
Evaluating Bayesian spatial methods for modelling species distributions with clumped and restricted occurrence data. [PDF]
PLoS ONE, 2017 Statistical approaches for inferring the spatial distribution of taxa (Species Distribution Models, SDMs) commonly rely on available occurrence data, which is often clumped and geographically restricted.
David W Redding +3 more
doaj +1 more source
Latent Gaussian modeling and INLA: A review with focus on space-time applications [PDF]
, 2016 Bayesian hierarchical models with latent Gaussian layers have proven very flexible in capturing complex stochastic behavior and hierarchical structures in high-dimensional spatial and spatio-temporal data.
Opitz, Thomas
core +2 more sources
Modeling multivariate positive‐valued time series using R‐INLA
Applied Stochastic Models in Business and IndustryAbstractIn this article, we describe fast Bayesian statistical analysis of vector positive‐valued time series, with application to interesting financial data streams. We discuss a flexible level correlated model (LCM) framework for building hierarchical models for vector positive‐valued time series.
Dutta, Chiranjit +2 more
openaire +2 more sources
Should you use data integration for your distribution model?
Journal of Animal Ecology, EarlyView.This paper explores cases where data integration (the joint modelling of two or more observational datasets) is useful for species distribution models, and also highlights cases where it's actually not useful. This provides the first concrete guidance for deciding whether or not data integration is worth your time.
Benjamin R. Goldstein +3 more
wiley +1 more source
Brazilian Journal of Infectious Diseases, 2020 Introduction: Use of antibiotic and bacterial resistance is the result of a complex interaction not completely understood. Objectives: To evaluate the impact of entire antimicrobial use (community plus hospitals) on the incidence of bloodstream ...
Ícaro Boszczowski +7 more
doaj +1 more source