32 resultados para b-value distribution
Resumo:
We propose a new kernel estimation of the cumulative distribution function based on transformation and on bias reducing techniques. We derive the optimal bandwidth that minimises the asymptotic integrated mean squared error. The simulation results show that our proposed kernel estimation improves alternative approaches when the variable has an extreme value distribution with heavy tail and the sample size is small.
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Flood simulation studies use spatial-temporal rainfall data input into distributed hydrological models. A correct description of rainfall in space and in time contributes to improvements on hydrological modelling and design. This work is focused on the analysis of 2-D convective structures (rain cells), whose contribution is especially significant in most flood events. The objective of this paper is to provide statistical descriptors and distribution functions for convective structure characteristics of precipitation systems producing floods in Catalonia (NE Spain). To achieve this purpose heavy rainfall events recorded between 1996 and 2000 have been analysed. By means of weather radar, and applying 2-D radar algorithms a distinction between convective and stratiform precipitation is made. These data are introduced and analyzed with a GIS. In a first step different groups of connected pixels with convective precipitation are identified. Only convective structures with an area greater than 32 km2 are selected. Then, geometric characteristics (area, perimeter, orientation and dimensions of the ellipse), and rainfall statistics (maximum, mean, minimum, range, standard deviation, and sum) of these structures are obtained and stored in a database. Finally, descriptive statistics for selected characteristics are calculated and statistical distributions are fitted to the observed frequency distributions. Statistical analyses reveal that the Generalized Pareto distribution for the area and the Generalized Extreme Value distribution for the perimeter, dimensions, orientation and mean areal precipitation are the statistical distributions that best fit the observed ones of these parameters. The statistical descriptors and the probability distribution functions obtained are of direct use as an input in spatial rainfall generators.
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Introducción y objetivos. Se ha señalado que, en la miocardiopatía hipertrófica (MCH), la desorganización de las fibras regionales da lugar a segmentos en los que la deformación es nula o está gravemente reducida, y que estos segmentos tienen una distribución no uniforme en el ventrículo izquierdo (VI). Esto contrasta con lo observado en otros tipos de hipertrofia como en el corazón de atleta o la hipertrofia ventricular izquierda hipertensiva (HVI-HT), en los que puede haber una deformación cardiaca anormal, pero nunca tan reducida como para que se observe ausencia de deformación. Así pues, proponemos el empleo de la distribución de los valores de strain para estudiar la deformación en la MCH. Métodos. Con el empleo de resonancia magnética marcada (tagged), reconstruimos la deformación sistólica del VI de 12 sujetos de control, 10 atletas, 12 pacientes con MCH y 10 pacientes con HVI-HT. La deformación se cuantificó con un algoritmo de registro no rígido y determinando los valores de strain sistólico máximo radial y circunferencial en 16 segmentos del VI. Resultados. Los pacientes con MCH presentaron unos valores medios de strain significativamente inferiores a los de los demás grupos. Sin embargo, aunque la deformación observada en los individuos sanos y en los pacientes con HVI-HT se concentraba alrededor del valor medio, en la MCH coexistían segmentos con contracción normal y segmentos con una deformación nula o significativamente reducida, con lo que se producía una mayor heterogeneidad de los valores de strain. Se observaron también algunos segmentos sin deformación incluso en ausencia de fibrosis o hipertrofia. Conclusiones. La distribución de strain caracteriza los patrones específicos de deformación miocárdica en pacientes con diferentes etiologías de la HVI. Los pacientes con MCH presentaron un valor medio de strain significativamente inferior, así como una mayor heterogeneidad de strain (en comparación con los controles, los atletas y los pacientes con HVI-HT), y tenían regiones sin deformación.
Resumo:
A method to estimate an extreme quantile that requires no distributional assumptions is presented. The approach is based on transformed kernel estimation of the cumulative distribution function (cdf). The proposed method consists of a double transformation kernel estimation. We derive optimal bandwidth selection methods that have a direct expression for the smoothing parameter. The bandwidth can accommodate to the given quantile level. The procedure is useful for large data sets and improves quantile estimation compared to other methods in heavy tailed distributions. Implementation is straightforward and R programs are available.
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The space subdivision in cells resulting from a process of random nucleation and growth is a subject of interest in many scientific fields. In this paper, we deduce the expected value and variance of these distributions while assuming that the space subdivision process is in accordance with the premises of the Kolmogorov-Johnson-Mehl-Avrami model. We have not imposed restrictions on the time dependency of nucleation and growth rates. We have also developed an approximate analytical cell size probability density function. Finally, we have applied our approach to the distributions resulting from solid phase crystallization under isochronal heating conditions
Resumo:
Plan recognition is the problem of inferring the goals and plans of an agent from partial observations of her behavior. Recently, it has been shown that the problem can be formulated and solved usingplanners, reducing plan recognition to plan generation.In this work, we extend this model-basedapproach to plan recognition to the POMDP setting, where actions are stochastic and states are partially observable. The task is to infer a probability distribution over the possible goals of an agent whose behavior results from a POMDP model. The POMDP model is shared between agent and observer except for the true goal of the agent that is hidden to the observer. The observations are action sequences O that may contain gaps as some or even most of the actions done by the agent may not be observed. We show that the posterior goal distribution P(GjO) can be computed from the value function VG(b) over beliefs b generated by the POMDPplanner for each possible goal G. Some extensionsof the basic framework are discussed, and a numberof experiments are reported.
Weak and Strong Altruism in Trait Groups: Reproductive Suicide, Personal Fitness, and Expected Value
Resumo:
A simple variant of trait group selection, employing predators as the mechanism underlying group selection, supports contingent reproductive suicide as altruism (i.e., behavior lowering personal fitness while augmenting that of another) without kin assortment. The contingent suicidal type may either saturate the population or be polymorphic with a type avoiding suicide, depending on parameters. In addition to contingent suicide, this randomly assorting morph may also exhibit continuously expressed strong altruism (sensu Wilson 1979) usually thought restricted to kin selection. The model will not, however, support a sterile worker caste as such, where sterility occurs before life history events associated with effective altruism; reproductive suicide must remain fundamentally contingent (facultative sensu West Eberhard 1987; Myles 1988) under random assortment. The continuously expressed strong altruism supported by the model may be reinterpreted as probability of arbitrarily committing reproductive suicide, without benefit for another; such arbitrary suicide (a "load" on "adaptive" suicide) is viable only under a more restricted parameter space relative to the necessarily concomitant adaptive contingent suicide.
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In this paper we propose a subsampling estimator for the distribution ofstatistics diverging at either known rates when the underlying timeseries in strictly stationary abd strong mixing. Based on our results weprovide a detailed discussion how to estimate extreme order statisticswith dependent data and present two applications to assessing financialmarket risk. Our method performs well in estimating Value at Risk andprovides a superior alternative to Hill's estimator in operationalizingSafety First portofolio selection.
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How much information does an auctioneer want bidders to have in a private value environment?We address this question using a novel approach to ordering information structures based on the property that in private value settings more information leads to a more disperse distribution of buyers updated expected valuations. We define the class of precision criteria following this approach and different notions of dispersion, and relate them to existing criteria of informativeness. Using supermodular precision, we obtain three results: (1) a more precise information structure yields a more efficient allocation; (2) the auctioneer provides less than the efficient level of information since more information increases bidder informational rents; (3) there is a strategic complementarity between information and competition, so that both the socially efficient and the auctioneer s optimal choice of precision increase with the number of bidders, and both converge as the number of bidders goes to infinity.
Resumo:
A simple variant of trait group selection, employing predators as themechanism underlying group selection, supports contingent reproductivesuicide as altruism (i.e., behavior lowering personal fitness whileaugmenting that of another) without kin assortment. The contingentsuicidal type may either saturate the population or be polymorphicwith a type avoiding suicide, depending on parameters. In addition tocontingent suicide, this randomly assorting morph may also exhibitcontinuously expressed strong altruism (sensu Wilson 1979) usuallythought restricted to kin selection. The model will not, however,support a sterile worker caste as such, where sterility occurs beforelife history events associated with effective altruism; reproductivesuicide must remain fundamentally contingent (facultative sensu WestEberhard 1987; Myles 1988) under random assortment. The continuouslyexpressed strong altruism supported by the model may be reinterpretedas probability of arbitrarily committing reproductive suicide, withoutbenefit for another; such arbitrary suicide (a "load" on "adaptive"suicide) is viable only under a more restricted parameter spacerelative to the necessarily concomitant adaptive contingent suicide.
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The distribution of single-particle strength in nuclear matter is calculated for a realistic nucleon-nucleon interaction. The influence of the short-range repulsion and the tensor component of the nuclear force on the spectral functions is to move approximately 13% of the total strength for all single-particle states beyond 100 MeV into the particle domain. This result is related to the abundantly observed quenching phenomena in nuclei which include the reduction of spectroscopic factors observed in (e,ep) reactions and the missing strength in low energy response functions.
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In this paper we consider diffusion of a passive substance C in a temporarily and spatially inhomogeneous two-dimensional medium. As a realization for the latter we choose a phase-separating medium consisting of two substances A and B, whose dynamics is determined by the Cahn-Hilliard equation. Assuming different diffusion coefficients of C in A and B, we find that the variance of the distribution function of the said substance grows less than linearly in time. We derive a simple identity for the variance using a probabilistic ansatz and are then able to identify the interface between A and B as the main cause for this nonlinear dependence. We argue that, finally, for very large times the here temporarily dependent diffusion "constant" goes like t-1/3 to a constant asymptotic value D¿. The latter is calculated approximately by employing the effective-medium approximation and by fitting the simulation data to the said time dependence.
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We study the exact ground state of the two-dimensional random-field Ising model as a function of both the external applied field B and the standard deviation ¿ of the Gaussian random-field distribution. The equilibrium evolution of the magnetization consists in a sequence of discrete jumps. These are very similar to the avalanche behavior found in the out-of-equilibrium version of the same model with local relaxation dynamics. We compare the statistical distributions of magnetization jumps and find that both exhibit power-law behavior for the same value of ¿. The corresponding exponents are compared.