919 resultados para Poisson Mixed Model
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica
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Dissertation to obtain PhD in Industrial Engineering
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Dissertação para obtenção do Grau de Doutor em Engenharia Química e Bioquímica
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INTRODUCTION: Malaria is a serious problem in the Brazilian Amazon region, and the detection of possible risk factors could be of great interest for public health authorities. The objective of this article was to investigate the association between environmental variables and the yearly registers of malaria in the Amazon region using Bayesian spatiotemporal methods. METHODS: We used Poisson spatiotemporal regression models to analyze the Brazilian Amazon forest malaria count for the period from 1999 to 2008. In this study, we included some covariates that could be important in the yearly prediction of malaria, such as deforestation rate. We obtained the inferences using a Bayesian approach and Markov Chain Monte Carlo (MCMC) methods to simulate samples for the joint posterior distribution of interest. The discrimination of different models was also discussed. RESULTS: The model proposed here suggests that deforestation rate, the number of inhabitants per km², and the human development index (HDI) are important in the prediction of malaria cases. CONCLUSIONS: It is possible to conclude that human development, population growth, deforestation, and their associated ecological alterations are conducive to increasing malaria risk. We conclude that the use of Poisson regression models that capture the spatial and temporal effects under the Bayesian paradigm is a good strategy for modeling malaria counts.
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This work presents a model and a heuristic to solve the non-emergency patients transport (NEPT) service issues given the new rules recently established in Portugal. The model follows the same principle of the Team Orienteering Problem by selecting the patients to be included in the routes attending the maximum reduction in costs when compared with individual transportation. This model establishes the best sets of patients to be transported together. The model was implemented in AMPL and a compact formulation was solved using NEOS Server. A heuristic procedure based on iteratively solving problems with one vehicle was presented, and this heuristic provides good results in terms of accuracy and computation time.
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Este proyecto propone extender y generalizar los procesos de estimación e inferencia de modelos aditivos generalizados multivariados para variables aleatorias no gaussianas, que describen comportamientos de fenómenos biológicos y sociales y cuyas representaciones originan series longitudinales y datos agregados (clusters). Se genera teniendo como objeto para las aplicaciones inmediatas, el desarrollo de metodología de modelación para la comprensión de procesos biológicos, ambientales y sociales de las áreas de Salud y las Ciencias Sociales, la condicionan la presencia de fenómenos específicos, como el de las enfermedades.Es así que el plan que se propone intenta estrechar la relación entre la Matemática Aplicada, desde un enfoque bajo incertidumbre y las Ciencias Biológicas y Sociales, en general, generando nuevas herramientas para poder analizar y explicar muchos problemas sobre los cuales tienen cada vez mas información experimental y/o observacional.Se propone, en forma secuencial, comenzando por variables aleatorias discretas (Yi, con función de varianza menor que una potencia par del valor esperado E(Y)) generar una clase unificada de modelos aditivos (paramétricos y no paramétricos) generalizados, la cual contenga como casos particulares a los modelos lineales generalizados, no lineales generalizados, los aditivos generalizados, los de media marginales generalizados (enfoques GEE1 -Liang y Zeger, 1986- y GEE2 -Zhao y Prentice, 1990; Zeger y Qaqish, 1992; Yan y Fine, 2004), iniciando una conexión con los modelos lineales mixtos generalizados para variables latentes (GLLAMM, Skrondal y Rabe-Hesketh, 2004), partiendo de estructuras de datos correlacionados. Esto permitirá definir distribuciones condicionales de las respuestas, dadas las covariables y las variables latentes y estimar ecuaciones estructurales para las VL, incluyendo regresiones de VL sobre las covariables y regresiones de VL sobre otras VL y modelos específicos para considerar jerarquías de variación ya reconocidas. Cómo definir modelos que consideren estructuras espaciales o temporales, de manera tal que permitan la presencia de factores jerárquicos, fijos o aleatorios, medidos con error como es el caso de las situaciones que se presentan en las Ciencias Sociales y en Epidemiología, es un desafío a nivel estadístico. Se proyecta esa forma secuencial para la construcción de metodología tanto de estimación como de inferencia, comenzando con variables aleatorias Poisson y Bernoulli, incluyendo los existentes MLG, hasta los actuales modelos generalizados jerárquicos, conextando con los GLLAMM, partiendo de estructuras de datos correlacionados. Esta familia de modelos se generará para estructuras de variables/vectores, covariables y componentes aleatorios jerárquicos que describan fenómenos de las Ciencias Sociales y la Epidemiología.
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Bursting Oscillation, Mixed-Mode oscillation, Slow Manifold, Quasi-Integral, slow-fast analysis, QSSA
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En aquest treball s’implementa un model analític de les característiques DC del MOSFET de doble porta (DG-MOSFET), basat en la solució de l’equació de Poisson i en la teoria de deriva-difussió[1]. El MOSFET de doble porta asimètric presenta una gran flexibilitat en el disseny de la tensió llindar i del corrent OFF. El model analític reprodueix les característiques DC del DG-MOSFET de canal llarg i és la base per construir models circuitals tipus SPICE.
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We propose a mixed finite element method for a class of nonlinear diffusion equations, which is based on their interpretation as gradient flows in optimal transportation metrics. We introduce an appropriate linearization of the optimal transport problem, which leads to a mixed symmetric formulation. This formulation preserves the maximum principle in case of the semi-discrete scheme as well as the fully discrete scheme for a certain class of problems. In addition solutions of the mixed formulation maintain exponential convergence in the relative entropy towards the steady state in case of a nonlinear Fokker-Planck equation with uniformly convex potential. We demonstrate the behavior of the proposed scheme with 2D simulations of the porous medium equations and blow-up questions in the Patlak-Keller-Segel model.
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We construct a new family of semi-discrete numerical schemes for the approximation of the one-dimensional periodic Vlasov-Poisson system. The methods are based on the coupling of discontinuous Galerkin approximation to the Vlasov equation and several finite element (conforming, non-conforming and mixed) approximations for the Poisson problem. We show optimal error estimates for the all proposed methods in the case of smooth compactly supported initial data. The issue of energy conservation is also analyzed for some of the methods.
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(Résumé de l'ouvrage) This volume addresses research topics within the field of Bhakti literature, the devotional poetry and other compositions of devotional character in the earlier literature of the modern South Asian languages. Its papers range from the roots of the Bhakti tradition in the early history of Krsna to its modern adaptations in nineteenth- and twentieth-century culture. Geographically, they span Bengal to Sind, Panjab to Maharashtra. Contemporary study of the modern Indian languages has broadened the scope of scholarship to consider today's Hindu attitudes, and those of a mixed society, against the background of ancient culture. Here, materials in six modern Asian languages are discussed: Bengali, Gujarati, Hindi in its main literary forms, Marathi, Panjabi and Sindhi; with assessment also of material in Sanskrit, Arabic and Chinese. In addition to studies of literary (and orally transmitted) works in the Krsna or Rama traditions, and of Sufi compositions and their interpretation, there are papers on the early history of sacred sites, the emergence of the religion of Rama, later religious formulations throughout the subcontinent, and the interaction of the Islamic and the Hindu.
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The population of industrialized societies has increased tremendously over the last century, raising the question on how an enhanced age affects cognition. The relevance of two models of healthy aging are contrasted in the present study that both target the functioning of the two cerebral hemispheres. The right hemi-aging model (RHAM) assumes that functions of the right hemisphere decline before those of the left hemisphere. The Hemispheric Asymmetry Reduction in Older Adults (HAROLD) Model suggests that the contralateral hemisphere supports the normally superior hemisphere in a given task resulting in a reduced hemispheric asymmetry overall. In a mixed design, 20 younger and 20 older adults performed both a task assessing a left (lateralized lexical decisions) and a right (sex decisions on chimeric faces) hemisphere advantage. Results indicated that lateralized performance in both tasks was attenuated in older as compared to younger adults, in particular in men. These observations support the HAROLD model. Future studies should investigate whether this reduced functional hemispheric asymmetry in older age results from compensatory processes or from a process of de-differentiation
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We introduce and analyze two new semi-discrete numerical methods for the multi-dimensional Vlasov-Poisson system. The schemes are constructed by combing a discontinuous Galerkin approximation to the Vlasov equation together with a mixed finite element method for the Poisson problem. We show optimal error estimates in the case of smooth compactly supported initial data. We propose a scheme that preserves the total energy of the system.
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This paper characterizes a mixed strategy Nash equilibrium in a one-dimensional Downsian model of two-candidate elections with a continuous policy space, where candidates are office motivated and one candidate enjoys a non-policy advantage over the other candidate. We assume that voters have quadratic preferences over policies and that their ideal points are drawn from a uniform distribution over the unit interval. In our equilibrium the advantaged candidate chooses the expected median voter with probability one and the disadvantaged candidate uses a mixed strategy that is symmetric around it. We show that this equilibrium exists if the number of voters is large enough relative to the size of the advantage.