Search results for "Integrated Nested Laplace Approximation"
showing 9 items of 9 documents
Geoestadística en regiones heterogéneas con distancia basada en el coste
2012
El germen de la presente tesis consistió en un problema aplicado, de ingeniería, al que pensamos que la Estadística como disciplina puede contribuir de manera significativa. Concretamente, se trata de la elaboración de mapas acústicos en entornos urbanos. Resuelto habitualmente de una manera determinista y aproximada, la valoración de la incertidumbre de los resultados es extremadamente deficiente en la mayoría de los casos reales. Este problema, siendo de naturaleza espacial, se puede ver como un problema de predicción geoestadística, a partir de un conjunto de observaciones de campo. La dificultad radica en que el fenómeno se sitúa en un entorno urbano, que posee una importante heterogene…
Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy)
2020
The plant-pathogenic bacterium Xylella fastidiosa was first reported in Europe in 2013, in the province of Lecce, Italy, where extensive areas were affected by the olive quick decline syndrome, caused by the subsp. pauca. In Alicante, Spain, almond leaf scorch, caused by X. fastidiosa subsp. multiplex, was detected in 2017. The effects of climatic and spatial factors on the geographic distribution of X. fastidiosa in these two infested regions in Europe were studied. The presence/absence data of X. fastidiosa in the official surveys were analyzed using Bayesian hierarchical models through the integrated nested Laplace approximation (INLA) methodology. Climatic covariates were obtained from …
Modeling accident risk at the road level through zero-inflated negative binomial models: A case study of multiple road networks
2021
Abstract This paper presents a case study carried out in multiple cities of the Valencian Community (Spain) to determine the effect of sociodemographic and road characteristics on traffic accident risk. The analyzes are performed at the road segment level, considering the linear network representing the road structure of each city as a spatial lattice. The number of accidents observed in each road segment from 2010 to 2019 is taken as the response variable, and a zero-inflated modeling approach is considered. Count overdispersion and spatial dependence are also accounted for. Despite the complexity and sparsity of the data, the fitted models performed considerably well, with few exceptions.…
Prediction and Surveillance Sampling Assessment in Plant Nurseries and Fields
2022
In this paper, we propose a structured additive regression (STAR) model for modeling the occurrence of a disease in fields or nurseries. The methodological approach involves a Gaussian field (GF) affected by a spatial process represented by an approximation to a Gaussian Markov random field (GMRF). This modeling allows the building of maps with prediction probabilities regarding the presence of a disease in plants using Bayesian kriging. The advantage of this modeling is its computational benefit when compared with known spatial hierarchical models and with the Bayesian inference based on Markov chain Monte Carlo (MCMC) methods. Inference through the use of the integrated nested Laplace app…
Modelling Inoculum Availability ofPlurivorosphaerella nawaein Persimmon Leaf Litter with Bayesian Beta Regression
2019
AbstractCircular leaf spot (CLS), caused byPlurivorosphaerella nawae, is a serious disease of persimmon (Diospyros kaki) inducing necrotic lesions on leaves, defoliation and fruit drop. Under Mediter-ranean conditions,P. nawaeforms pseudothecia in the leaf litter during winter and ascospores are released in spring infecting susceptible leaves. Persimmon growers are advised to apply fungicides for CLS control during the period of inoculum availability, which was defined based on ascospore counts under the microscope. A model of inoculum availability ofP. nawaewas developed and evaluated as an alternative to ascospore counts. Leaf litter samples were collected weekly in L’Alcúdia from 2010 to…
Spatio-Temporal Modeling of Zika and Dengue Infections within Colombia
2018
The aim of this study is to estimate the parallel relative risk of Zika virus disease (ZVD) and dengue using spatio-temporal interaction effects models for one department and one city of Colombia during the 2015&ndash
Accounting for preferential sampling in species distribution models
2019
D. C., A. L. Q. and F. M. would like to thank the Ministerio de Educación y Ciencia (Spain) for financial support (jointly financed by the European Regional Development Fund) via Research Grants MTM2013‐42323‐P and MTM2016‐77501‐P, and ACOMP/2015/202 from Generalitat Valenciana (Spain). Species distribution models (SDMs) are now being widely used in ecology for management and conservation purposes across terrestrial, freshwater, and marine realms. The increasing interest in SDMs has drawn the attention of ecologists to spatial models and, in particular, to geostatistical models, which are used to associate observations of species occurrence or abundance with environmental covariates in a fi…
Spatial seismic point pattern analysis with Integrated Nested Laplace Approximation
2020
This paper proposes the use of Integrated Nested Laplace Approximation (Rue et al., 2009) to describe the spatial displacement of earthquake data. Specifying a hiechical structure of the data and parameters, an inhomogeneuos Log-Gaussian Cox Processes model is applied for describing seismic events occurred in Greece, an area of seismic hazard. In this way, the dependence of the spatial point process on external covariates can be taken into account, as well as the interaction among points, through the estimation of the parameters of the covariance of the Gaussian Random Field, with a computationally efficient approach.
Bayesian Analysis of Population Health Data
2021
The analysis of population-wide datasets can provide insight on the health status of large populations so that public health officials can make data-driven decisions. The analysis of such datasets often requires highly parameterized models with different types of fixed and random effects to account for risk factors, spatial and temporal variations, multilevel effects and other sources on uncertainty. To illustrate the potential of Bayesian hierarchical models, a dataset of about 500,000 inhabitants released by the Polish National Health Fund containing information about ischemic stroke incidence for a 2-year period is analyzed using different types of models. Spatial logistic regression and…