973 resultados para Gaussian Probability Distribution


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We apply the concept of exchangeable random variables to the case of non-additive robability distributions exhibiting ncertainty aversion, and in the lass generated bya convex core convex non-additive probabilities, ith a convex core). We are able to rove two versions of the law of arge numbers (de Finetti's heorems). By making use of two efinitions. of independence we rove two versions of the strong law f large numbers. It turns out that e cannot assure the convergence of he sample averages to a constant. e then modal the case there is a true" probability distribution ehind the successive realizations of the uncertain random variable. In this case convergence occurs. This result is important because it renders true the intuition that it is possible "to learn" the "true" additive distribution behind an uncertain event if one repeatedly observes it (a sufficiently large number of times). We also provide a conjecture regarding the "Iearning" (or updating) process above, and prove a partia I result for the case of Dempster-Shafer updating rule and binomial trials.

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In this paper we prove convergence to chaotic sunspot equilibrium through two learning rules used in the bounded rationality literature. The rst one shows the convergence of the actual dynamics generated by simple adaptive learning rules to a probability distribution that is close to the stationary measure of the sunspot equilibrium; since this stationary measure is absolutely continuous it results in a robust convergence to the stochastic equilibrium. The second one is based on the E-stability criterion for testing stability of rational expectations equilibrium, we show that the conditional probability distribution de ned by the sunspot equilibrium is expectational stable under a reasonable updating rule of this parameter. We also report some numerical simulations of the processes proposed.

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Este trabalho explora um importante conceito desenvolvido por Breeden & Litzenberger para extrair informações contidas nas opções de juros no mercado brasileiro (Opção Sobre IDI), no âmbito da Bolsa de Valores, Mercadorias e Futuros de São Paulo (BM&FBOVESPA) dias antes e após a decisão do COPOM sobre a taxa Selic. O método consiste em determinar a distribuição de probabilidade através dos preços das opções sobre IDI, após o cálculo da superfície de volatilidade implícita, utilizando duas técnicas difundidas no mercado: Interpolação Cúbica (Spline Cubic) e Modelo de Black (1976). Serão analisados os quatro primeiros momentos da distribuição: valor esperado, variância, assimetria e curtose, assim como suas respectivas variações.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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

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O conhecimento do modelo de distribuição espacial de pragas na cultura é fundamental para estabelecer um plano adequado de amostragem seqüencial e, assim, permitir a correta utilização das estratégias de controle e a otimização das técnicas de amostragem. Esta pesquisa objetivou estudar a distribuição espacial de lagartas de Alabama argillacea (Hübner) na cultura do algodoeiro, cultivar CNPA ITA-90. A coleta de dados ocorreu durante o ano agrícola de 1998/99 na Fazenda Itamarati Sul S.A., localizada no município de Ponta Porã, MS, em três diferentes áreas de 10.000 m² cada uma. Cada área amostral foi composta de 100 parcelas com 100 m² cada. Foi realizada semanalmente a contagem das lagartas pequenas, médias e grandes, encontradas em cinco plantas por parcela. Os índices de agregação (razão variância/média e índice de Morisita), o teste de qui-quadrado com o ajuste dos valores encontrados e esperados às distribuições teóricas de freqüência (Poisson, binomial positiva e binomial negativa), mostraram que todos os estádios das lagartas estão distribuídos de acordo com o modelo de distribuição contagiosa, ajustando-se ao padrão da Distribuição Binomial Negativa durante todo o período de infestação.

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Currently, one of the biggest challenges for the field of data mining is to perform cluster analysis on complex data. Several techniques have been proposed but, in general, they can only achieve good results within specific areas providing no consensus of what would be the best way to group this kind of data. In general, these techniques fail due to non-realistic assumptions about the true probability distribution of the data. Based on this, this thesis proposes a new measure based on Cross Information Potential that uses representative points of the dataset and statistics extracted directly from data to measure the interaction between groups. The proposed approach allows us to use all advantages of this information-theoretic descriptor and solves the limitations imposed on it by its own nature. From this, two cost functions and three algorithms have been proposed to perform cluster analysis. As the use of Information Theory captures the relationship between different patterns, regardless of assumptions about the nature of this relationship, the proposed approach was able to achieve a better performance than the main algorithms in literature. These results apply to the context of synthetic data designed to test the algorithms in specific situations and to real data extracted from problems of different fields

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A linear chain do not present phase transition at any finite temperature in a one dimensional system considering only first neighbors interaction. An example is the Ising ferromagnet in which his critical temperature lies at zero degree. Analogously, in percolation like disordered geometrical systems, the critical point is given by the critical probability equals to one. However, this situation can be drastically changed if we consider long-range bonds, replacing the probability distribution by a function like . In this kind of distribution the limit α → ∞ corresponds to the usual first neighbor bond case. In the other hand α = 0 corresponds to the well know "molecular field" situation. In this thesis we studied the behavior of Pc as a function of a to the bond percolation specially in d = 1. Our goal was to check a conjecture proposed by Tsallis in the context of his Generalized Statistics (a generalization to the Boltzmann-Gibbs statistics). By this conjecture, the scaling laws that depend with the size of the system N, vary in fact with the quantitie

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Injection-limited operation is identified in thin-film, alpha-NPD-based diodes. A detailed model for the impedance of the injection process is provided which considers the kinetics of filling/releasing of interface states as the key factor behind the injection mechanism. The injection model is able to simultaneously account for the steady-state, current-voltage (J-V) characteristics and impedance response. and is based on the sequential injection of holes mediated by energetically distributed surface states at the metal-organic interface. The model takes into account the vacuum level offset caused by the interface dipole, along with the partial shift of the interface level distribution with bias voltage. This approach connects the low-frequency (similar to 1 Hz) capacitance spectra, which exhibits a transition between positive to negative values, to the change in the occupancy of interface states with voltage. Simulations based on the model allow to derive the density of interface states effectively intervening in the carrier injection (similar to 5 x 10(12) cm(-2)), which exhibit a Gaussian-like distribution. A kinetically determined hole barrier is calculated at levels located similar to 0.4 eV below the contact work function. (C) 2008 Elsevier B.V. All rights reserved.

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In this work we elaborate and discuss a Complex Network model which presents connectivity scale free probability distribution (power-law degree distribution). In order to do that, we modify the rule of the preferential attachment of the Bianconi-Barabasi model, including a factor which represents the similarity of the sites. The term that corresponds to this similarity is called the affinity, and is obtained by the modulus of the difference between the fitness (or quality) of the sites. This variation in the preferential attachment generates very interesting results, by instance the time evolution of the connectivity, which follows a power-law distribution ki / ( t t0 )fi, where fi indicates the rate to the site gain connections. Certainly this depends on the affinity with other sites. Besides, we will show by numerical simulations results for the average path length and for the clustering coefficient

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Complex systems have stimulated much interest in the scientific community in the last twenty years. Examples this area are the Domany-Kinzel cellular automaton and Contact Process that are studied in the first chapter this tesis. We determine the critical behavior of these systems using the spontaneous-search method and short-time dynamics (STD). Ours results confirm that the DKCA e CP belong to universality class of Directed Percolation. In the second chapter, we study the particle difusion in two models of stochastic sandpiles. We characterize the difusion through diffusion constant D, definite through in the relation h(x)2i = 2Dt. The results of our simulations, using finite size scalling and STD, show that the diffusion constant can be used to study critical properties. Both models belong to universality class of Conserved Directed Percolation. We also study that the mean-square particle displacement in time, and characterize its dependence on the initial configuration and particle density. In the third chapter, we introduce a computacional model, called Geographic Percolation, to study watersheds, fractals with aplications in various areas of science. In this model, sites of a network are assigned values between 0 and 1 following a given probability distribution, we order this values, keeping always its localization, and search pk site that percolate network. Once we find this site, we remove it from the network, and search for the next that has the network to percole newly. We repeat these steps until the complete occupation of the network. We study the model in 2 and 3 dimension, and compare the bidimensional case with networks form at start real data (Alps e Himalayas)

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The effect of changes in the bulk dielectric constant on the DNA torsional properties was evaluated from plasmid circularization reactions. In these reactions, pUC18 previously linearized by EcoRI digestion was recircularized with T4 DNA ligase. The bulk dielectric constant of the reaction medium was decreased by the addition of different concentrations of neutral solutes: ethylene glycol, glycerol, sorbitol, and sucrose, or increased by the addition of glycine. The topoisomers generated by the ligase reaction were resolved by agarose-gel electrophoresis. The DNA twist energy parameter (K), which is an apparent torsional constant, was determined by linearization of the Gaussian topoisomers' distribution. It was observed that the twist energy parameter for the given solutes is almost linearly dependent on the bulk dielectric constant. In the reaction buffer, the twist energy parameter was determined to be 1100 +/- 100. By decreasing the dielectric constant to 74 with the addition of sorbitol, the value of the parameter reaches K = 900 +/- 100, whereas the addition of ethylene glycol leads to kappa = 400 +/- 50. Upon addition of glycine, which resulted in a dielectric constant equal to 91, the value of the twist energy parameter increased to K 1750 +/- 100. (c) 2007 Wiley Periodicals.

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A Wigner function associated with the Rogers-Szego polynomials is proposed and its properties are discussed. It is shown that from such a Wigner function it is possible to obtain well-behaved probability distribution functions for both angle and action variables, defined on the compact support -pi less than or equal to theta < pi, and for m greater than or equal to 0, respectively. The width of the angle probability density is governed by the free parameter q characterizing the polynomials.

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In this paper, we discuss the tunneling time of a quantum particle through a rectangular barrier. The reflection and transmission times associated with the wave packets representing the particle are discussed. By using an initial Gaussian momentum distribution, we carry out a comparative analysis of the stationary phases of the incident, reflected, and transmitted wave packets leading to the reflection and transmission times at, and Delta t(T), respectively. In the present treatment of this old and very known problem we take into account the deformations of the reflected and transmitted momentum distributions. These deformations produce a dependence of the reflection and transmission times on the location of the initial wave packet. In a parallel calculation, by numerically monitoring the time evolution of the system, we characterize a reflection and a transmission time. Such times agree with the ones obtained via the stationary phase method. [S1050-2947(98)07912-8].

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The distribution of short-circuit current is investigated by means of two methods, one direct and the other analytic; both methods consider uniform probability distribution of line faults. In the direct method, the procedure consists of calculating fault currents at equidistant points along the line, starting from one of the end points and considering the other end open. The magnitude of the current is classified according to Brazilian standards (regulation NBR-7118). The analytic method assumes that the distribution of short-circuit currents through the busbar and the distribution of the line length connected to it are known, as well as the independence of values. The method is designed to determine the probability that fault currents through a line will surpass the pre-established magnitude, thus generating frequency distribution curves of short-circuit currents along the lines.