Spatial and spatio-temporal models with R-INLA
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The Integrated Nested Laplace Approximation approach has been developed as a computationally efficient alternative to MCMC and the availability of an R package (R-INLA) allows researchers to easily apply this method.About:
This article is published in Spatial and Spatio-temporal Epidemiology.The article was published on 2013-03-01 and is currently open access. It has received 396 citations till now. The article focuses on the topics: Markov chain Monte Carlo.read more
Citations
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Bayesian spatio-temporal modelling of anchovy abundance through the SPDE Approach
TL;DR: In this article, a flexible Bayesian hierarchical spatio-temporal model for zero-inflated positive continuous data is proposed to investigate the Peruvian anchovy dynamics across years, giving solid statistical support to many descriptive ecological studies.
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Prediction of humpback whale group densities along the Brazilian coast using spatial autoregressive models
TL;DR: In this article, the authors evaluated the influence of environmental factors (bathymetry and distance from shore with quadratic terms, and wind speed), effort, and spatial autocorrelation effects to predict humpback whale group density in the Southwest Atlantic Ocean.
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The New Dominator of the World: Modeling the Global Distribution of the Japanese Beetle under Land Use and Climate Change Scenarios
TL;DR: In this paper , the authors used the integrated nested Laplace approximation with a stochastic partial differential equation to identify areas of potential invasion and predict the distribution of the Japanese beetle.
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Geographical coincidence and mimicry between harmless snakes (Colubridae: Oxyrhopus) and harmful models (Elapidae: Micrurus)
TL;DR: Mimicry complexes may capitalize upon model signal diversity, allowing for the diversification of lineages with warning coloration in the face of stabilizing selection, and may not rely upon perfect signal matching and distributional overlap as previously supposed.
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Examining socio-economic factors to understand the hospital case fatality rates of COVID-19 in the city of São Paulo, Brazil.
Camila Lorenz,Patricia Marques Moralejo Bermudi,Breno Souza de Aguiar,Marcelo Antunes Failla,Tatiana Natasha Toporcov,Francisco Chiaravalloti-Neto,Ligia Vizeu Barrozo +6 more
TL;DR: In this article, the variability in hospital case fatality rates (HCFRs) of COVID-19 in relation to spatial inequalities in socio-economic factors, hospital health sector and patient medical condition across the city of Sao Paulo, Brazil was examined.
References
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Bayesian measures of model complexity and fit
TL;DR: In this paper, the authors consider the problem of comparing complex hierarchical models in which the number of parameters is not clearly defined and derive a measure pD for the effective number in a model as the difference between the posterior mean of the deviances and the deviance at the posterior means of the parameters of interest, which is related to other information criteria and has an approximate decision theoretic justification.
Book
Statistics for spatial data
Noel A Cressie,Noel A Cressie +1 more
TL;DR: In this paper, the authors present a survey of statistics for spatial data in the field of geostatistics, including spatial point patterns and point patterns modeling objects, using Lattice Data and spatial models on lattices.
Book
Monte Carlo Statistical Methods
TL;DR: This new edition contains five completely new chapters covering new developments and has sold 4300 copies worldwide of the first edition (1999).
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5. Statistics for Spatial Data
Mike Rees,N. Cressie +1 more
TL;DR: Cressie et al. as discussed by the authors presented the Statistics for Spatial Data (SDS) for the first time in 1991, and used it for the purpose of statistical analysis of spatial data.