438 resultados para Estimateur de Bayes
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We investigate the evolutionary history of the greater white-toothed shrew across its distribution in northern Africa and mainland Europe using sex-specific (mtDNA and Y chromosome) and biparental (X chromosome) markers. All three loci confirm a large divergence between eastern (Tunisia and Sardinia) and western (Morocco and mainland Europe) lineages, and application of a molecular clock to mtDNA divergence estimates indicates a more ancient separation (2.25 M yr ago) than described by some previous studies, supporting claims for taxonomic revision. Moroccan ancestry for the mainland European population is inconclusive from phylogenetic trees, but is supported by greater nucleotide diversity and a more ancient population expansion in Morocco than in Europe. Signatures of rapid population expansion in mtDNA, combined with low X and Y chromosome diversity, suggest a single colonization of mainland Europe by a small number of Moroccan shrews >38 K yr ago. This study illustrates that multilocus genetic analyses can facilitate the interpretation of species' evolutionary history but that phylogeographic inference using X and Y chromosomes is restricted by low levels of observed polymorphism.
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BACKGROUND: The estimation of demographic parameters from genetic data often requires the computation of likelihoods. However, the likelihood function is computationally intractable for many realistic evolutionary models, and the use of Bayesian inference has therefore been limited to very simple models. The situation changed recently with the advent of Approximate Bayesian Computation (ABC) algorithms allowing one to obtain parameter posterior distributions based on simulations not requiring likelihood computations. RESULTS: Here we present ABCtoolbox, a series of open source programs to perform Approximate Bayesian Computations (ABC). It implements various ABC algorithms including rejection sampling, MCMC without likelihood, a Particle-based sampler and ABC-GLM. ABCtoolbox is bundled with, but not limited to, a program that allows parameter inference in a population genetics context and the simultaneous use of different types of markers with different ploidy levels. In addition, ABCtoolbox can also interact with most simulation and summary statistics computation programs. The usability of the ABCtoolbox is demonstrated by inferring the evolutionary history of two evolutionary lineages of Microtus arvalis. Using nuclear microsatellites and mitochondrial sequence data in the same estimation procedure enabled us to infer sex-specific population sizes and migration rates and to find that males show smaller population sizes but much higher levels of migration than females. CONCLUSION: ABCtoolbox allows a user to perform all the necessary steps of a full ABC analysis, from parameter sampling from prior distributions, data simulations, computation of summary statistics, estimation of posterior distributions, model choice, validation of the estimation procedure, and visualization of the results.
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Etude des modèles de Whittle markoviens probabilisés Résumé Le modèle de Whittle markovien probabilisé est un modèle de champ spatial autorégressif simultané d'ordre 1 qui exprime simultanément chaque variable du champ comme une moyenne pondérée aléatoire des variables adjacentes du champ, amortie d'un coefficient multiplicatif ρ, et additionnée d'un terme d'erreur (qui est une variable gaussienne homoscédastique spatialement indépendante, non mesurable directement). Dans notre cas, la moyenne pondérée est une moyenne arithmétique qui est aléatoire du fait de deux conditions : (a) deux variables sont adjacentes (au sens d'un graphe) avec une probabilité 1 − p si la distance qui les sépare est inférieure à un certain seuil, (b) il n'y a pas d'adjacence pour des distances au-dessus de ce seuil. Ces conditions déterminent un modèle d'adjacence (ou modèle de connexité) du champ spatial. Un modèle de Whittle markovien probabilisé aux conditions où p = 0 donne un modèle de Whittle classique qui est plus familier en géographie, économétrie spatiale, écologie, sociologie, etc. et dont ρ est le coefficient d'autorégression. Notre modèle est donc une forme probabilisée au niveau de la connexité du champ de la forme des modèles de Whittle classiques, amenant une description innovante de l'autocorrélation spatiale. Nous commençons par décrire notre modèle spatial en montrant les effets de la complexité introduite par le modèle de connexité sur le pattern de variances et la corrélation spatiale du champ. Nous étudions ensuite la problématique de l'estimation du coefficent d'autorégression ρ pour lequel au préalable nous effectuons une analyse approfondie de son information au sens de Fisher et de Kullback-Leibler. Nous montrons qu'un estimateur non biaisé efficace de ρ possède une efficacité qui varie en fonction du paramètre p, généralement de manière non monotone, et de la structure du réseau d'adjacences. Dans le cas où la connexité du champ est non observée, nous montrons qu'une mauvaise spécification de l'estimateur de maximum de vraisemblance de ρ peut biaiser celui-ci en fonction de p. Nous proposons dans ce contexte d'autres voies pour estimer ρ. Pour finir, nous étudions la puissance des tests de significativité de ρ pour lesquels les statistiques de test sont des variantes classiques du I de Moran (test de Cliff-Ord) et du I de Moran maximal (en s'inspirant de la méthode de Kooijman). Nous observons la variation de puissance en fonction du paramètre p et du coefficient ρ, montrant par cette voie la dualité de l'autocorrélation spatiale entre intensité et connectivité dans le contexte des modèles autorégressifs
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Highway agencies spend millions of dollars to ensure safe and efficient winter travel. However, the effectiveness of winter-weather maintenance practices on safety and mobility are somewhat difficult to quantify. Safety and Mobility Impacts of Winter Weather - Phase 1 investigated opportunities for improving traffic safety on state-maintained roads in Iowa during winter-weather conditions. In Phase 2, three Iowa Department of Transportation (DOT) high-priority sites were evaluated and realistic maintenance and operations mitigation strategies were also identified. In this project, site prioritization techniques for identifying roadway segments with the potential for safety improvements related to winter-weather crashes, were developed through traditional naïve statistical methods by using raw crash data for seven winter seasons and previously developed metrics. Additionally, crash frequency models were developed using integrated crash data for four winter seasons, with the objective of identifying factors that affect crash frequency during winter seasons and screening roadway segments using the empirical Bayes technique. Based on these prioritization techniques, 11 sites were identified and analyzed in conjunction with input from Iowa DOT district maintenance managers and snowplow operators and the Iowa DOT Road Weather Information System (RWIS) coordinator.
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Treball final de carrera basat en el reconeixement de punts clau en imatges mitjançant l'algorisme Random Ferns.
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The fire ant Solenopsis invicta is a significant pest that was inadvertently introduced into the southern United States almost a century ago and more recently into California and other regions of the world. An assessment of genetic variation at a diverse set of molecular markers in 2144 fire ant colonies from 75 geographic sites worldwide revealed that at least nine separate introductions of S. invicta have occurred into newly invaded areas and that the main southern U.S. population is probably the source of all but one of these introductions. The sole exception involves a putative serial invasion from the southern United States to California to Taiwan. These results illustrate in stark fashion a severe negative consequence of an increasingly massive and interconnected global trade and travel system.
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O objetivo deste trabalho foi realizar uma análise bayesiana de modelos auto-regressivos de ordem p, AR(p), para dados em painel referentes às diferenças esperadas nas progênies (DEP) de touros da raça Nelore publicados de 2000 a 2006. Neste trabalho, adotou-se o modelo AR(2), indicado pela análise prévia da função de autocorrelação parcial. As comparações entre as prioris, realizadas por meio do Fator de Bayes e do Pseudo-Fator de Bayes, indicaram superioridade da priori independente t-Student multivariada - Gama inversa em relação à priori hierárquica Normal multivariada - Gama inversa e a priori de Jeffreys. Os resultados indicam a importância de se dividir os animais em grupos homogêneos de acordo com a acurácia. Constatou-se também que, em média, a eficiência de previsão dos valores de DEP para um ano futuro foi próxima de 80%.
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Standard practice of wave-height hazard analysis often pays little attention to the uncertainty of assessed return periods and occurrence probabilities. This fact favors the opinion that, when large events happen, the hazard assessment should change accordingly. However, uncertainty of the hazard estimates is normally able to hide the effect of those large events. This is illustrated using data from the Mediterranean coast of Spain, where the last years have been extremely disastrous. Thus, it is possible to compare the hazard assessment based on data previous to those years with the analysis including them. With our approach, no significant change is detected when the statistical uncertainty is taken into account. The hazard analysis is carried out with a standard model. Time-occurrence of events is assumed Poisson distributed. The wave-height of each event is modelled as a random variable which upper tail follows a Generalized Pareto Distribution (GPD). Moreover, wave-heights are assumed independent from event to event and also independent of their occurrence in time. A threshold for excesses is assessed empirically. The other three parameters (Poisson rate, shape and scale parameters of GPD) are jointly estimated using Bayes' theorem. Prior distribution accounts for physical features of ocean waves in the Mediterranean sea and experience with these phenomena. Posterior distribution of the parameters allows to obtain posterior distributions of other derived parameters like occurrence probabilities and return periods. Predictives are also available. Computations are carried out using the program BGPE v2.0
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O objetivo deste trabalho foi propor uma abordagem bayesiana do método de Eberhart & Russell para avaliar a adaptabilidade e da estabilidade fenotípica de genótipos de alfafa (Medicago sativa), bem como avaliar a eficiência da utilização de distribuições a priori informativas e pouco informativas. Foram utilizados dados de um experimento em blocos ao acaso, no qual se avaliou a produção de massa de matéria seca de 92 genótipos. A metodologia bayesiana proposta foi implementada no programa livre R por meio da função MCMCregress do pacote MCMCpack. Para representar as distribuições a priori pouco informativas, utilizaram-se distribuições de probabilidade com grande variância; e, para representar distribuições a priori informativas, adotou-se o conceito de meta-análise, que se caracteriza pela utilização de informações provenientes de trabalhos anteriores. A comparação entre as distribuições a priori foi realizada por meio do fator de Bayes, com a função BayesFactor do pacote MCMCpack, que indicou a priori informativa como a mais adequada nas condições deste estudo.
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This paper presents a Bayesian approach to the design of transmit prefiltering matrices in closed-loop schemes robust to channel estimation errors. The algorithms are derived for a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Two different optimizationcriteria are analyzed: the minimization of the mean square error and the minimization of the bit error rate. In both cases, the transmitter design is based on the singular value decomposition (SVD) of the conditional mean of the channel response, given the channel estimate. The performance of the proposed algorithms is analyzed,and their relationship with existing algorithms is indicated. As withother previously proposed solutions, the minimum bit error rate algorithmconverges to the open-loop transmission scheme for very poor CSI estimates.
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Resumo:O objetivo deste trabalho foi selecionar, sob a perspectiva bayesiana, genótipos de feijão-caupi (Vigna unguiculata) que reúnam alta adaptabilidade e estabilidade fenotípicas, no Estado do Mato Grosso do Sul. Foram utilizados dados de quatro experimentos, conduzidos em delineamento de blocos ao acaso, em que a produtividade de grãos de 20 genótipos de feijão-caupi semiprostrado foi avaliada. Para representar as distribuições a priori pouco informativas, utilizaram-se distribuições de probabilidade com grande variância; e, para representar distribuições a priori informativas, adotou-se o conceito de metanálise, com uso de informações de trabalhos anteriores. A comparação entre as distribuições a priori foi realizada por meio do fator de Bayes. A abordagem bayesiana proporciona maior acurácia na seleção de genótipos de feijão-caupi semiprostrado, com elevadas adaptabilidade e estabilidade fenotípicas avaliadas por meio da metodologia de Eberhart & Russell. Com base nas prioris informativas, os genótipos MNC99-507G-4, TE97-309G-24, MNC99-542F-7 e BR 17-Gurguéia são classificados como de alta adaptabilidade a ambientes favoráveis. Já os genótipos TE96-290-12G, MNC99-510F-16, MNC99-508G-1, MNC99-541F-21, MNC99-542F-5 e MNC99-547F-2 apresentam alta adaptabilidade a ambientes desfavoráveis.
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L'objet de ce travail est l'évaluation de l'activité de radionucléides présents à l'état de traces, par exemple dans l'environnement. Lorsque les mesures sont de courte durée, ou si les sources sont peu actives, l'analyse statistique standard ne donne plus une estimation fiable de l'activité et de son incertitude. L'introduction du concept bayesien d'a priori permet de modéliser l'information à disposition de l'observateur avant qu'il effectue la mesure. Cette information conduit à une estimation plus cohérente des grandeurs physiques recherchées. Le cadre de la théorie est tout d'abord présenté, définissant les concepts d'état, d'observation et de décision. La mesure physique est traduite par un modèle statistique qui est une probabilité de transition des états vers les observations. L'information de Fisher et celle de Shannon-Kullback sont introduites dans le but d'obtenir les a priori nécessaires au théorème de Bayes. Les modèles propres à la mesure de la radioactivité sont ensuite traités. Si l'on peut considérer l'activité comme constante, le modèle est celui de Poisson et conduit à des a priori de type gamma. Pour les grandes activités, ces deux lois se rapprochent des gaussiennes et l'on retrouve l'analyse statistique classique. Lorsque la décroissance du nombre de noyaux n'est plus négligeable, ou lors de l'évaluation de certains temps d'attente, d'autres modèles sont développés. Quelques applications sont présentées ensuite, notamment une définition cohérente des intervalles de confiance et l'estimation de l'activité de radionucléides à schéma complexe par spectrométrie gamma, où l'obtention de tout un spectre permet une analyse multidimensionnelle. Le paradigme bayesien conduit à une répartition complète et globale pour l'état du système physique mesuré. L'observateur obtient ainsi la meilleure estimation possible de l'état basée sur son modèle d'expérience et l'information préalable en sa possession.
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Geophysical data may provide crucial information about hydrological properties, states, and processes that are difficult to obtain by other means. Large data sets can be acquired over widely different scales in a minimally invasive manner and at comparatively low costs, but their effective use in hydrology makes it necessary to understand the fidelity of geophysical models, the assumptions made in their construction, and the links between geophysical and hydrological properties. Geophysics has been applied for groundwater prospecting for almost a century, but it is only in the last 20 years that it is regularly used together with classical hydrological data to build predictive hydrological models. A largely unexplored venue for future work is to use geophysical data to falsify or rank competing conceptual hydrological models. A promising cornerstone for such a model selection strategy is the Bayes factor, but it can only be calculated reliably when considering the main sources of uncertainty throughout the hydrogeophysical parameter estimation process. Most classical geophysical imaging tools tend to favor models with smoothly varying property fields that are at odds with most conceptual hydrological models of interest. It is thus necessary to account for this bias or use alternative approaches in which proposed conceptual models are honored at all steps in the model building process.
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BACKGROUND: Major factors influencing the phenotypic diversity of a lineage can be recognized by characterizing the extent and mode of trait evolution between related species. Here, we compared the evolutionary dynamics of traits associated with floral morphology and climatic preferences in a clade composed of the genera Codonanthopsis, Codonanthe and Nematanthus (Gesneriaceae). To test the mode and specific components that lead to phenotypic diversity in this group, we performed a Bayesian phylogenetic analysis of combined nuclear and plastid DNA sequences and modeled the evolution of quantitative traits related to flower shape and size and to climatic preferences. We propose an alternative approach to display graphically the complex dynamics of trait evolution along a phylogenetic tree using a wide range of evolutionary scenarios. RESULTS: Our results demonstrated heterogeneous trait evolution. Floral shapes displaced into separate regimes selected by the different pollinator types (hummingbirds versus insects), while floral size underwent a clade-specific evolution. Rates of evolution were higher for the clade that is hummingbird pollinated and experienced flower resupination, compared with species pollinated by bees, suggesting a relevant role of plant-pollinator interactions in lowland rainforest. The evolution of temperature preferences is best explained by a model with distinct selective regimes between the Brazilian Atlantic Forest and the other biomes, whereas differentiation along the precipitation axis was characterized by higher rates, compared with temperature, and no regime or clade-specific patterns. CONCLUSIONS: Our study shows different selective regimes and clade-specific patterns in the evolution of morphological and climatic components during the diversification of Neotropical species. Our new graphical visualization tool allows the representation of trait trajectories under parameter-rich models, thus contributing to a better understanding of complex evolutionary dynamics.
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BACKGROUND: Available methods to simulate nucleotide or amino acid data typically use Markov models to simulate each position independently. These approaches are not appropriate to assess the performance of combinatorial and probabilistic methods that look for coevolving positions in nucleotide or amino acid sequences. RESULTS: We have developed a web-based platform that gives a user-friendly access to two phylogenetic-based methods implementing the Coev model: the evaluation of coevolving scores and the simulation of coevolving positions. We have also extended the capabilities of the Coev model to allow for the generalization of the alphabet used in the Markov model, which can now analyse both nucleotide and amino acid data sets. The simulation of coevolving positions is novel and builds upon the developments of the Coev model. It allows user to simulate pairs of dependent nucleotide or amino acid positions. CONCLUSIONS: The main focus of our paper is the new simulation method we present for coevolving positions. The implementation of this method is embedded within the web platform Coev-web that is freely accessible at http://coev.vital-it.ch/, and was tested in most modern web browsers.