Results 111 to 120 of about 14,253 (214)

Improving the INLA approach for approximate Bayesian inference for latent Gaussian models

open access: yes, 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

Trends in Meningitis Burden and Projections to 2040: A Secondary Analysis of the Global Burden of Disease Study 2023

open access: yesHealth Science Reports, Volume 9, Issue 5, May 2026.
ABSTRACT Background and Aims Meningitis remains a global health challenge, characterized by substantial regional and etiologic disparities. This study aimed to analyze recent trends, forecast future burden, and examine the influence of development status on meningitis outcomes.
Mehdi Azizmohammad Looha   +4 more
wiley   +1 more source

Epidemiological Features and Temporal Trends of Five Common Sexually Transmitted Infections Excluding HIV, 1990–2021: Findings From the Global Burden of Disease Study

open access: yesJournal of Medical Virology, Volume 98, Issue 5, May 2026.
ABSTRACT Sexually transmitted infections (STIs) remain a major global health threat. A comprehensive assessment of their epidemiological features and future trajectories is essential for informing targeted public health policies and achieving international control targets.
Baigong Feng   +5 more
wiley   +1 more source

New opportunities for grassland species in warming temperate winters

open access: yesFunctional Ecology, Volume 40, Issue 5, Page 1138-1150, May 2026.
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

An Efficient Bayesian Inference Framework for Coalescent-Based Nonparametric Phylodynamics

open access: yes, 2014
Phylodynamics focuses on the problem of reconstructing past population size dynamics from current genetic samples taken from the population of interest.
Karcher, Michael   +4 more
core   +2 more sources

Environmental drivers of metapopulation dynamics throughout the full annual cycle in a declining Arctic‐nesting migratory herbivore

open access: yesJournal of Animal Ecology, Volume 95, Issue 5, Page 865-881, May 2026.
We provide a framework for extending commonly used integrated population models to a metapopulation framework for testing novel ecological hypotheses about how changing environmental conditions within and among subpopulations drive changes in animal abundance.
Alexander R. Schindler   +5 more
wiley   +1 more source

Interpretable statistics for complex modelling: quantile and topological learning [PDF]

open access: yes, 2019
As the complexity of our data increased exponentially in the last decades, so has our need for interpretable features. This thesis revolves around two paradigms to approach this quest for insights.
Padellini, Tullia
core  

Generalisations of Fisher Matrices

open access: yes, 2016
Fisher matrices play an important role in experimental design and in data analysis. Their primary role is to make predictions for the inference of model parameters - both their errors and covariances.
Heavens, Alan
core   +2 more sources

Processing Spatial Data for Statistical Modeling and Visualization Case study: INLA model for COVID-19 in Alabama, USA

open access: yesActa Technica Jaurinensis
This research emphasizes the visualization of spatial data for statistical modelling and analysis of the relative risk associated with the COVID-19 pandemic in Alabama, USA. We used Bayesian analysis and the Integrated Nested Laplace Approximation (INLA)
Getachew Engidaw, György Terdik
doaj   +1 more source

Estimating the marginal likelihood with Integrated nested Laplace approximation (INLA)

open access: yes, 2016
The marginal likelihood is a well established model selection criterion in Bayesian statistics. It also allows to efficiently calculate the marginal posterior model probabilities that can be used for Bayesian model averaging of quantities of interest.
Hubin, Aliaksandr, Storvik, Geir
openaire   +2 more sources

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