Results 51 to 60 of about 3,995 (142)
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
International Journal of Applied Mathematics, Sciences, and Technology for National DefenseThe number of malaria cases in Indonesia has increased in recent years. The highest malaria cases in Indonesia are in the eastern region, namely Papua Province, where in 2021 there were 86,022 cases.
Kirana Azzahra +2 more
doaj +1 more source
Cadernos de Saúde Pública, 2013 This study aimed to analyze the spatial distribution of dengue risk and its association with socio-environmental conditions. This was an ecological study of the counts of autochthonous dengue cases in the municipality of Campinas, São Paulo State, Brazil,
José Vilton Costa +2 more
doaj +1 more source
Crime Science, 2022 Near-repeat victimization patterns have made predictive models for burglaries possible. While the models have been implemented in different countries, the results obtained have not always been in line with initial expectations; to the point where their ...
Pere Boqué, Marc Saez, Laura Serra
doaj +1 more source
An Extended Laplace Approximation Method for Bayesian Inference of Self-Exciting Spatial-Temporal Models of Count Data [PDF]
, 2017 Self-Exciting models are statistical models of count data where the probability of an event occurring is influenced by the history of the process. In particular, self-exciting spatio-temporal models allow for spatial dependence as well as temporal self ...
Clark, Nicholas +2 more
core +2 more sources
Coherent Disaggregation and Uncertainty Quantification for Spatially Misaligned Data
Environmetrics, Volume 37, Issue 2, March 2026.ABSTRACT Spatial misalignment arises when datasets are aggregated or collected at different spatial scales, leading to information loss. We develop a Bayesian disaggregation framework that links misaligned data to a continuous‐domain model through an iteratively linearised integration scheme implemented with the Integrated Nested Laplace Approximation (
Man Ho Suen, Mark Naylor, Finn Lindgren
wiley +1 more source
EconometricsWe compare three modern Bayesian approaches, Hamiltonian Monte Carlo (HMC), Variational Bayes (VB), and Integrated Nested Laplace Approximation (INLA), for two classic spatial econometric specifications: the spatial lag model and spatial error model. Our
Yuheng Ling, Julie Le Gallo
doaj +1 more source
Frontiers in Public Health, 2022 BackgroundBefore major non-pharmaceutical interventions were implemented, seasonal incidence of influenza in Hong Kong showed a rapid and unexpected reduction immediately following the early spread of COVID-19 in mainland China in January 2020.
Chun-Pang Lin +6 more
doaj +1 more source
, 2017 We develop a stochastic modeling approach based on spatial point processes of log-Gaussian Cox type for a collection of around 5000 landslide events provoked by a precipitation trigger in Sicily, Italy.
Huser, Raphael +2 more
core +1 more source
Scandinavian Journal of Statistics, Volume 53, Issue 1, Page 364-394, March 2026.ABSTRACT Latent Gaussian models (LGMs) are a subset of Bayesian Hierarchical models where Gaussian priors, conditional on variance parameters, are assigned to all effects in the model. LGMs are employed in many fields for their flexibility and computational efficiency. However, practitioners find prior elicitation on the variance parameters challenging
Luisa Ferrari, Massimo Ventrucci
wiley +1 more source