960 resultados para Spatial models


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This note investigates the adequacy of the finite-sample approximation provided by the Functional Central Limit Theorem (FCLT) when the errors are allowed to be dependent. We compare the distribution of the scaled partial sums of some data with the distribution of the Wiener process to which it converges. Our setup is purposely very simple in that it considers data generated from an ARMA(1,1) process. Yet, this is sufficient to bring out interesting conclusions about the particular elements which cause the approximations to be inadequate in even quite large sample sizes.

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Cet article illustre l’applicabilité des méthodes de rééchantillonnage dans le cadre des tests multiples (simultanés), pour divers problèmes économétriques. Les hypothèses simultanées sont une conséquence habituelle de la théorie économique, de sorte que le contrôle de la probabilité de rejet de combinaisons de tests est un problème que l’on rencontre fréquemment dans divers contextes économétriques et statistiques. À ce sujet, on sait que le fait d’ignorer le caractère conjoint des hypothèses multiples peut faire en sorte que le niveau de la procédure globale dépasse considérablement le niveau désiré. Alors que la plupart des méthodes d’inférence multiple sont conservatrices en présence de statistiques non-indépendantes, les tests que nous proposons visent à contrôler exactement le niveau de signification. Pour ce faire, nous considérons des critères de test combinés proposés initialement pour des statistiques indépendantes. En appliquant la méthode des tests de Monte Carlo, nous montrons comment ces méthodes de combinaison de tests peuvent s’appliquer à de tels cas, sans recours à des approximations asymptotiques. Après avoir passé en revue les résultats antérieurs sur ce sujet, nous montrons comment une telle méthodologie peut être utilisée pour construire des tests de normalité basés sur plusieurs moments pour les erreurs de modèles de régression linéaires. Pour ce problème, nous proposons une généralisation valide à distance finie du test asymptotique proposé par Kiefer et Salmon (1983) ainsi que des tests combinés suivant les méthodes de Tippett et de Pearson-Fisher. Nous observons empiriquement que les procédures de test corrigées par la méthode des tests de Monte Carlo ne souffrent pas du problème de biais (ou sous-rejet) souvent rapporté dans cette littérature – notamment contre les lois platikurtiques – et permettent des gains sensibles de puissance par rapport aux méthodes combinées usuelles.

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Fire is a major management issue in the southwestern United States. Three spatial models of fire risk for Coconino County, Northern Arizona. These models were generated using thematic data layers depicting vegetation, elevation, wind speed and direction, and precipitation for January (winter), June (summer), and July (start of monsoon season). ArcGIS 9.0 was used to weight attributes in raster layers to reflect their influence on fire risk and to interpolate raster data layers from point data. Final models were generated using the raster calculator in the Spatial Analyst extension of ArcGIS 9.0. Ultimately, the unique combinations of variables resulted in three different models illustrating the change in fire risk during the year.

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Neste trabalho, foi realizado um estudo de mapeamento de áreas de incidência e previsões para os casos de dengue na área urbana de Belém. Para as previsões foi utilizada à incidência de dengue com a precipitação pluviométrica a partir de modelos estatísticos, baseados na metodologia de Box e Jenkins de series temporais. O período do estudo foi de 05 anos (2007-2011). Na pesquisa temos métodos multivariados de series temporais, com uso de função de transferência e modelos espaciais, em que se analisou a existência de autocorrelações espaciais na variável em estudo. Os resultados das análises dos dados de incidência de casos de dengue e precipitação mostraram que, o aumento no número de casos de dengue acompanha o aumento na precipitação, demonstrando a relação direta entre o número de casos de dengue e a precipitação nos anos em estudo. O modelo de previsão construído para a incidência de casos de dengue apresentou um bom ajuste com resultados satisfatórios podendo, neste caso, ser utilizado na previsão da dengue. Em relação à análise espacial, foi possível uma visualização da incidência de casos na área urbana de Belém, com as respectivas áreas de incidência, mostrando os níveis de significância em porcentagem. Para o período estudado observou-se o comportamento e as variações dos casos de dengue, com destaque para quatro bairros: Marco, Guamá, Pedreira e Tapanã, com possíveis influências destes bairros nas áreas (bairros) vizinhas. Portanto, o presente estudo evidencia a contribuição para o planejamento das ações de controle da dengue, ao servir de instrumento no apoio às decisões na área de saúde pública.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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This paper proposed a two-dimensional spatial model to describe the adaptive immune response for viral hepatitis B. This model considered six populations: healthy hepatocytes T, infected hepatocytes Y , hepatitis B virus V , innate immune system I, active immune system X and memory cells, X. First, a compartmental model was constructed and its equilibrium solutions and also the threshold values related to the stability of each solution were obtained. Using this model, we was able to reproduce the different trends observed for the disease, which are: individuals that eliminate the infection without forming immune response, patients with acute and chronic carriers. By including dispersion of defense cells of the immune system and virus (spatial model), we analyze two situations: homogeneous model, in which the model parameters are the same at all points of the network, and heterogeneous model, which characterizes cells more permeable and less permeable to virus invasion. For the two spatial models (homogeneous and heterogeneous) the times relatead to the viral erradication and/or virus invasion and persistence becoming smaller in relation to the compartmental model. The results also showed that for the set of values used in the simulations and if the two diffusion rates are different from zero, the model is sensitive to variations in the rate of viral spread and not dependent on the dispersion of memory cells. Finally, the heterogeneous model when compared to the homogeneous model shows that the infection can be spatially limited depending on the type of the cell involved in the infection process

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Analytical methods accounting for imperfect detection are often used to facilitate reliable inference in population and community ecology. We contend that similar approaches are needed in disease ecology because these complicated systems are inherently difficult to observe without error. For example, wildlife disease studies often designate individuals, populations, or spatial units to states (e.g., susceptible, infected, post-infected), but the uncertainty associated with these state assignments remains largely ignored or unaccounted for. We demonstrate how recent developments incorporating observation error through repeated sampling extend quite naturally to hierarchical spatial models of disease effects, prevalence, and dynamics in natural systems. A highly pathogenic strain of avian influenza virus in migratory waterfowl and a pathogenic fungus recently implicated in the global loss of amphibian biodiversity are used as motivating examples. Both show that relatively simple modifications to study designs can greatly improve our understanding of complex spatio-temporal disease dynamics by rigorously accounting for uncertainty at each level of the hierarchy.

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Landscape structure and heterogeneity play a potentially important, but little understood role in predator-prey interactions and behaviourally-mediated habitat selection. For example, habitat complexity may either reduce or enhance the efficiency of a predator's efforts to search, track, capture, kill and consume prey. For prey, structural heterogeneity may affect predator detection, avoidance and defense, escape tactics, and the ability to exploit refuges. This study, investigates whether and how vegetation and topographic structure influence the spatial patterns and distribution of moose (Alces alces) mortality due to predation and malnutrition at the local and landscape levels on Isle Royale National Park. 230 locations where wolves (Canis lupus) killed moose during the winters between 2002 and 2010, and 182 moose starvation death sites for the period 1996-2010, were selected from the extensive Isle Royale Wolf-Moose Project carcass database. A variety of LiDAR-derived metrics were generated and used in an algorithm model (Random Forest) to identify, characterize, and classify three-dimensional variables significant to each of the mortality classes. Furthermore, spatial models to predict and assess the likelihood at the landscape scale of moose mortality were developed. This research found that the patterns of moose mortality by predation and malnutrition across the landscape are non-random, have a high degree of spatial variability, and that both mechanisms operate in contexts of comparable physiographic and vegetation structure. Wolf winter hunting locations on Isle Royale are more likely to be a result of its prey habitat selection, although they seem to prioritize the overall areas with higher moose density in the winter. Furthermore, the findings suggest that the distribution of moose mortality by predation is habitat-specific to moose, and not to wolves. In addition, moose sex, age, and health condition also affect mortality site selection, as revealed by subtle differences between sites in vegetation heights, vegetation density, and topography. Vegetation density in particular appears to differentiate mortality locations for distinct classes of moose. The results also emphasize the significance of fine-scale landscape and habitat features when addressing predator-prey interactions. These finer scale findings would be easily missed if analyses were limited to the broader landscape scale alone.

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Although the nature of the blood groups A and B has been comprehensively studied for a long time, it is still unclear as to what exactly is the epitope that is recognized by antibodies having AB specificity, i.e. monoclonal and polyclonal antibodies which are capable of interacting equally well with the antigens GalNAcalpha 1-3(Fucalpha 1-2)Gal (A trisaccharide) and Galalpha 1-3(Fucalpha 1-2)Gal (B trisaccharide), but do not react with their common fragment Fucalpha 1-2Gal. We have supposed that besides Fucalpha 1-2Gal, A and B antigens have one more shared epitope. The trisaccharides A and B are practically identical from the conformational point of view, the only difference being situated at position 2 of Galalpha residue, i.e. trisaccharide A has a NHAc group, whereas trisaccharide B has a hydroxyl group (see formulas). We have hypothesized that the AB-epitope should be situated in the part of the molecule that is opposite to the NHAc group of GalNAc residue. In order to test this hypothesis we have synthesized a polymeric conjugate in such a way that de-N-acetylated A-trisaccharide is attached to a polymer via the nitrogen in position C-2 of the galactosamine residue. In this conjugate the supposed AB-epitope should be maximally accessible for antibodies from the solution, whereas the discrimination site of antigens A and B by the antibodies should be maximally hidden due to the close proximity of the polymer. Interaction with several anti-AB monoclonal antibodies revealed that a part of them really interacted with the synthetic AB-glycotope, thus confirming our hypothesis. Moreover, similar antibodies were revealed in the blood of healthy blood group 0 donors. Analysis of spatial models was performed in addition to identify the hydroxyl groups of Fuc, Galalpha, and Galbeta residues, which are particularly involved in the composition of the AB-glycotope.

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This paper analyzes whether the Congressional budget process (instituted in 1974) leads to lower aggregate spending than does the piece-meal appropriations process that preceded it. Previous theoretical analysis, using spatial models of legislator preferences, is inconclusive. This paper uses a model of interest group lobbying, where a legislature determines spending on a national public good and on subsidies to subsets of the population that belong to nationwide sector-specific interest groups. In the appropriations process, the Appropriations Committee proposes a budget, maximizing the joint welfare of voters and the interest groups, that leads to overspending on subsidies. In the budget process, a Budget Committee proposes an aggregate level of spending (the budget resolution); the Appropriations Committee then proposes a budget. If the lobby groups are not subject to a binding resource constraint, the two institutional structures lead to identical outcomes. With such a constraint, however, there is a free rider problem among the groups in lobbying the Budget Committee, as each group only obtains a small fraction of the benefits from increasing the aggregate budget. If the number of groups is sufficiently large, each takes the budget resolution as given, and lobbies only the Appropriations Committee. The main results are that aggregate spending is lower, and social welfare higher, under the budget process; however, provision of the public good is suboptimal. The paper also presents two extensions: the first endogenizes the enforcement of the budget resolution by incorporating the relevant procedural rules into the model. The second analyzes statutory budget rules that limit spending levels, but can be revised by a simple majority vote. In each case,the free rider problem prevents the groups from securing the required changes to procedural and budget rules.

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El concepto “desarrollo sustentable" se ha consolidado en la academia, organismos internacionales e instituciones públicas que tienen como una preocupación central el bienestar colectivo o la calidad de vida de la población. También está presente en el discurso de partidos políticos, organizaciones no gubernamentales, movimientos sociales y otros actores de la sociedad civil, que buscan nuevas respuestas a distintos problemas que aquejan a la sociedad y que dicen relación con su estrategia de desarrollo. De esta forma, se trata de un concepto universalmente aceptado y legitimado, aunque su significado no siempre sea unívoco y no conlleve en todos los casos al mismo tipo de acciones. Su fortaleza, sin embargo, radica en su concepción ampliamente compartida como uno de los meta - objetivos de la sociedad. No obstante, tal vez una de las mayores debilidades del concepto sea su (todavía) baja aplicabilidad a la realidad. Como dice Reboratti (2000:202), “desarrollo sostenible es...una meta a alcanzar, una posibilidad que aparece en el futuro y que tal vez nunca alcanzaremos...", pero según reconoce el mismo autor, requiere de al menos un esfuerzo de planificación, que –según entendemos nosotros- ha de contar con herramientas específicas, que permitan encauzar en forma efectiva el desarrollo de un territorio hacia su sustentabilidad. En este contexto, resulta fundamental desarrollar una metodología de ordenamiento territorial que pueda conducir efectivamente a un desarrollo sustentable. Por cierto, es necesario que dicha metodología sea de fácil aplicación, de manera que se constituya en un apoyo eficiente y eficaz para las instituciones responsables de la planificación y administración del territorio. En virtud de lo anterior, el presente trabajo tiene como objetivo general exponer una metodología para la elaboración de un Plan de Ordenamiento Territorial, basada en el concepto de “sustentabilidad", que sea efectiva y simple en su aplicación. Los componentes centrales de esta propuesta metodológica son: (a) la integración de distintas herramientas de análisis para el diagnóstico evaluativo de un territorio, (b) la ponderación de todas las dimensiones de la sustentabilidad, (c) la proposición de instrumentos para el diseño de modelos espaciales que permitan encauzar el desarrollo de un territorio hacia su sustentabilidad, considerando el uso racional de los recursos naturales, la reducción de los riesgos de desastres y el mejoramiento de la calidad de vida de las generaciones presentes y futuras. La metodología propuesta ha sido aplicada a un caso de estudio de escala local, la comuna de San José de Maipo en Santiago de Chile, a través de un ejercicio docente desarrollado por los alumnos de la promoción 2007 en el Taller de Gestión Ambiental, del Magíster en Asentamientos Humanos y Medio Ambiente de la Pontificia Universidad Católica de Chile. El proceso metodológico propuesto considera básicamente dos subprocesos: el diagnóstico evaluativo del sistema territorial y el diseño de un modelo territorial, cuyo resultado es la elaboración de un Plan de Ordenamiento Territorial Sustentable para la comuna de San José de Maipo.

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En el presente trabajo realizamos un aproximación mediante el análisis basado en la sintaxis espacial aplicado al espacio doméstico de las sociedades de la edad del Hierro de la franja central de la Iberia Mediterránea, entre los siglos VI y III a. C. En una primera sección se introduce la importancia de la configuración de las casas para comprender la sociedad ibérica. A continuación seleccionamos algunos ejemplos de la mitad meridional del País Valenciano para realizar nuestro análisis. Se identifican de dos modelos espaciales claramente definidos. Por último se relacionan estos esquemas constructivos con los procesos de agregación de unidades familiares para constituir las comunidades ibéricas.

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Biotic interactions can have large effects on species distributions yet their role in shaping species ranges is seldom explored due to historical difficulties in incorporating biotic factors into models without a priori knowledge on interspecific interactions. Improved SDMs, which account for biotic factors and do not require a priori knowledge on species interactions, are needed to fully understand species distributions. Here, we model the influence of abiotic and biotic factors on species distribution patterns and explore the robustness of distributions under future climate change. We fit hierarchical spatial models using Integrated Nested Laplace Approximation (INLA) for lagomorph species throughout Europe and test the predictive ability of models containing only abiotic factors against models containing abiotic and biotic factors. We account for residual spatial autocorrelation using a conditional autoregressive (CAR) model. Model outputs are used to estimate areas in which abiotic and biotic factors determine species’ ranges. INLA models containing both abiotic and biotic factors had substantially better predictive ability than models containing abiotic factors only, for all but one of the four species. In models containing abiotic and biotic factors, both appeared equally important as determinants of lagomorph ranges, but the influences were spatially heterogeneous. Parts of widespread lagomorph ranges highly influenced by biotic factors will be less robust to future changes in climate, whereas parts of more localised species ranges highly influenced by the environment may be less robust to future climate. SDMs that do not explicitly include biotic factors are potentially misleading and omit a very important source of variation. For the field of species distribution modelling to advance, biotic factors must be taken into account in order to improve the reliability of predicting species distribution patterns both presently and under future climate change.

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Este artículo comprueba la existencia de autocorrelación espacial al considerar la proporción de personas que viven en situación de miseria en los municipios del departamento de Antioquia, Colombia. Para ello se utiliza el test I de Moran y se propone un algoritmo para descartar la posibilidad de que la dependencia espacial sea espuria. Los resultados demuestran la necesidad de tener en cuenta la econometría espacial para determinar la asignación óptima del gasto social, destinado a intervenir en forma efectiva la situación de miseria en los municipios del departamento de Antioquia

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Leaf wetness duration (LWD) models based on empirical approaches offer practical advantages over physically based models in agricultural applications, but their spatial portability is questionable because they may be biased to the climatic conditions under which they were developed. In our study, spatial portability of three LWD models with empirical characteristics - a RH threshold model, a decision tree model with wind speed correction, and a fuzzy logic model - was evaluated using weather data collected in Brazil, Canada, Costa Rica, Italy and the USA. The fuzzy logic model was more accurate than the other models in estimating LWD measured by painted leaf wetness sensors. The fraction of correct estimates for the fuzzy logic model was greater (0.87) than for the other models (0.85-0.86) across 28 sites where painted sensors were installed, and the degree of agreement k statistic between the model and painted sensors was greater for the fuzzy logic model (0.71) than that for the other models (0.64-0.66). Values of the k statistic for the fuzzy logic model were also less variable across sites than those of the other models. When model estimates were compared with measurements from unpainted leaf wetness sensors, the fuzzy logic model had less mean absolute error (2.5 h day(-1)) than other models (2.6-2.7 h day(-1)) after the model was calibrated for the unpainted sensors. The results suggest that the fuzzy logic model has greater spatial portability than the other models evaluated and merits further validation in comparison with physical models under a wider range of climate conditions. (C) 2010 Elsevier B.V. All rights reserved.