Listar Artículos de revista INAMAT2 - INAMAT2 aldizkari artikuluak por tema "INLA"
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Alleviating confounding in spatio-temporal areal models with an application on crimes against women in India
Assessing associations between a response of interest and a set of covariates in spatial areal models is the leitmotiv of ecological regression. However, the presence of spatially correlated random effects can mask or even ... -
Bayesian inference in multivariate spatio-temporal areal models using INLA: analysis of gender-based violence in small areas
Multivariate models for spatial count data are currently receiving attention in disease mapping to model two or more diseases jointly. They have been thoroughly studied from a theoretical point of view, but their use in ... -
Flexible Bayesian P-splines for smoothing age-specific spatio-temporal mortality patterns
In this paper age-space-time models based on one and two-dimensional P-splines with B-spline bases are proposed for smoothing mortality rates, where both xed relative scale and scale invariant two-dimensional penalties ... -
In spatio-temporal disease mapping models, identifiability constraints affect PQL and INLA results
Disease mapping studies the distribution of relative risks or rates in space and time, and typically relies on generalized linear mixed models (GLMMs) including fixed effects and spatial, temporal, and spatio-temporal ... -
Multivariate Bayesian spatio-temporal P-spline models to analyze crimes against women
Univariate spatio-temporal models for areal count data have received great attention in recent years for estimating risks. However, models for studying multivariate responses are less commonly used mainly due to the ... -
Space-time analysis of ovarian cancer mortality rates by age groups in Spanish provinces (1989-2015)
Background: Ovarian cancer is a silent and largely asymptomatic cancer, leading to late diagnosis and worse prognosis. The late-stage detection and low survival rates, makes the study of the space-time evolution of ovarian ... -
Space-time interactions in bayesian disease mapping with recent tools: making things easier for practitioners
Spatio-temporal disease mapping studies the distribution of mortality or incidence risks in space and its evolution in time, and it usually relies on fitting hierarchical Poisson mixed models. These models are complex for ... -
Using mortality to predict incidence for rare and lethal cancers in very small areas
Incidence and mortality figures are needed to get a comprehensive overview of cancer burden. In many countries, cancer mortality figures are routinely recorded by statistical offices, whereas incidence depends on regional ...