931 resultados para Maxwell s deduction of the statistical distribution


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Power law distributions, a well-known model in the theory of real random variables, characterize a wide variety of natural and man made phenomena. The intensity of earthquakes, the word frequencies, the solar ares and the sizes of power outages are distributed according to a power law distribution. Recently, given the usage of power laws in the scientific community, several articles have been published criticizing the statistical methods used to estimate the power law behaviour and establishing new techniques to their estimation with proven reliability. The main object of the present study is to go in deep understanding of this kind of distribution and its analysis, and introduce the half-lives of the radioactive isotopes as a new candidate in the nature following a power law distribution, as well as a \canonical laboratory" to test statistical methods appropriate for long-tailed distributions.

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The present research studies the spatial patterns of the distribution of the Swiss population (DSP). This description is carried out using a wide variety of global spatial structural analysis tools such as topological, statistical and fractal measures, which enable the estimation of the spatial degree of clustering of a point pattern. A particular attention is given to the analysis of the multifractality to characterize the spatial structure of the DSP at different scales. This will be achieved by measuring the generalized q-dimensions and the singularity spectrum. This research is based on high quality data of the Swiss Population Census of the Year 2000 at a hectometric resolution (grid 100 x 100 m) issued by the Swiss Federal Statistical Office (FSO).

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El objetivo de la presente investigación fue analizar la correspondencia entre los resultados de una evaluación de tierras con la distribución real de los cultivos. Para ello la aptitud biofísica de las tierras se comparó con diferentes tipologías de frecuencia de ocurrencia de los cultivos y rotaciones derivadas de mapas de cultivos multitemporales. La investigación fue llevada a cabo en el distrito de riego de Flumen (33.000 ha), localizado en el valle del Ebro (NE España). La evaluación de tierras se basó en una cartografía de suelos 1:100.000, según el esquema FAO, para los principales cultivos presentes en el área de estudio (alfalfa, cereales de invierno, maíz, arroz y girasol). Se utilizaron tres mapas de frecuencia de cultivos y un mapa de rotaciones, derivado de una serie temporal de imágenes Landsat TM y ETM+ del periodo 1993-2000, y se compararon con los mapas de aptitud de tierras para los diferentes cultivos. Se analizó estadísticamente (Pearson χ2, Cramer V, Gamma y Somers D) la relación entre los dos tipos de variables. Los resultados muestran la existencia de una relación significativa (P=0,001) entre la localización de los cultivos y la idoneidad de las tierras, excepto de cultivos oportunistas como el girasol, muy influenciado por las subvenciones en el periodo estudiado. Las rotaciones basadas en la alfalfa muestran los mayores porcentajes (52%) de ocupación en las tierrass aptas para la agricultura en el área de estudio. El presente enfoque multitemporal de análisis de la información ofrece una visión más real que la comparación entre un mapa de evaluación de tierras y un mapa de cultivos de una fecha determinada, cuando se valora el grado de acuerdo entre las recomendaciones sobre la aptitud de las tierras y los cultivos realmente cultivados por los agricultores.

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AimOur aim was to understand the interplay of heterogeneous climatic and spatial landscapes in shaping the distribution of nuclear microsatellite variation in burrowing parrots, Cyanoliseus patagonus. Given the marked phenotypic differences between populations of burrowing parrots we hypothesized an important role of geographical as well climatic heterogeneity in the population structure of this species. LocationSouthern South America. MethodsWe applied a landscape genetics approach to investigate the explicit patterns of genetic spatial autocorrelation based on both geography and climate using spatial principal component analysis (sPCA). This necessitated a novel statistical estimation of the species climatic landscape, considering temperature- and precipitation-based variables separately to evaluate their weight in shaping the distribution of genetic variation in our model system. ResultsGeographical and climatic heterogeneity successfully explained molecular variance in burrowing parrots. sPCA divided the species distribution into two main areas, Patagonia and the pre-Andes, which were connected by an area of geographical and climatic transition. Moreover, sPCA revealed cryptic and conservation-relevant genetic structure: the pre-Andean populations and the transition localities were each divided into two groups, each management units for conservation. Main conclusionssPCA, a method originally developed for spatial genetics, allowed us to unravel the genetic structure related to spatial and climatic landscapes and to visualize these patterns in landscape space. These novel climatic inferences underscore the importance of our modified sPCA approach in revealing how climatic variables can drive cryptic patterns of genetic structure, making the approach potentially useful in the study of any species distributed over a climatically heterogeneous landscape.

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The effect of the heat flux on the rate of chemical reaction in dilute gases is shown to be important for reactions characterized by high activation energies and in the presence of very large temperature gradients. This effect, obtained from the second-order terms in the distribution function (similar to those obtained in the Burnett approximation to the solution of the Boltzmann equation), is derived on the basis of information theory. It is shown that the analytical results describing the effect are simpler if the kinetic definition for the nonequilibrium temperature is introduced than if the thermodynamic definition is introduced. The numerical results are nearly the same for both definitions

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Habitat-based statistical models relating patterns of presence and absence of species to habitat variables could be useful to resolve conservation-related problems and highlight the causes of population declines. In this paper, we apply such a modelling approach to an endemic amphibian, the Sardinian mountain newt Euproctus platycephalus, considered by IUCN a critically endangered species. Sardinian newts inhabit freshwater habitat in streams, small lakes and pools on the island of Sardinia (Italy). Reported declines of newt populations are not yet supported by quantitative data, however, they are perceived or suspected across the species' historical range. This study represents a first attempt trying to statistically relate habitat characteristics to Sardinian newt occurrence and persistence. Linear regression analysis revealed that newts are more likely to be found in sites with colder water temperature, less riparian vegetation and, marginally, absence of fish. The implications of the results for the conservation of the species are discussed, and suggestions for the short-term management of newt inhabited sites suggested. (C) 2003 Elsevier Ltd. All rights reserved.

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In this paper we perform an analytical and numerical study of Extreme Value distributions in discrete dynamical systems. In this setting, recent works have shown how to get a statistics of extremes in agreement with the classical Extreme Value Theory. We pursue these investigations by giving analytical expressions of Extreme Value distribution parameters for maps that have an absolutely continuous invariant measure. We compare these analytical results with numerical experiments in which we study the convergence to limiting distributions using the so called block-maxima approach, pointing out in which cases we obtain robust estimation of parameters. In regular maps for which mixing properties do not hold, we show that the fitting procedure to the classical Extreme Value Distribution fails, as expected. However, we obtain an empirical distribution that can be explained starting from a different observable function for which Nicolis et al. (Phys. Rev. Lett. 97(21): 210602, 2006) have found analytical results.

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The number of bidders, N, involved in a construction procurement auction is known to have an important effect on the value of the lowest bid and the mark-up applied by bidders. In practice, for example, it is important for a bidder to have a good estimate of N when bidding for a current contract. One approach, instigated by Friedman in 1956, is to make such an estimate by statistical analysis and modelling. Since then, however, finding a suitable model for N has been an enduring problem for researchers and, despite intensive research activity in the subsequent 30 years, little progress has been made, due principally to the absence of new ideas and perspectives. The debate is resumed by checking old assumptions, providing new evidence relating to concomitant variables and proposing a new model. In doing this and in order to ensure universality, a novel approach is developed and tested by using a unique set of 12 construction tender databases from four continents. This shows the new model provides a significant advancement on previous versions. Several new research questions are also posed and other approaches identified for future study.

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The distribution of masses for neutron stars is analysed using the Bayesian statistical inference, evaluating the likelihood of the proposed Gaussian peaks by using 54 measured points obtained in a variety of systems. The results strongly suggest the existence of a bimodal distribution of the masses, with the first peak around 1.37 M(circle dot) and a much wider second peak at 1.73 M(circle dot). The results support earlier views related to the different evolutionary histories of the members for the first two peaks, which produces a natural separation (even if no attempt to `label` the systems has been made here). They also accommodate the recent findings of similar to M(circle dot) masses quite naturally. Finally, we explore the existence of a subgroup around 1.25 M(circle dot), finding weak, if any, evidence for it. This recently claimed low-mass subgroup, possibly related to the O-Mg-Ne core collapse events, has a monotonically decreasing likelihood and does not stand out clearly from the rest of the sample.

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In this paper we present an extension of the generalized Birnbaum-Saunders distribution family introduced in [Diaz-Garcia, J.A., Leiva-Sanchez, V., 2005. A new family of life distributions based on the contoured elliptically distributions. Journal of Statistical Planning and Inference 128 (2), 445-457] with a view to make it even more flexible in terms of its kurtosis coefficient. Properties involving moments and asymmetry and kurtosis indexes are studied for some special members of this family such as the slash Birnbaum-Saunders and slash-t Birnbaum-Saunders. Simulation studies for some particular cases and a real data analysis are also reported, illustrating the usefulness of the extension considered. (C) 2008 Elsevier B.V. All rights reserved.

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This thesis contributes to the heuristic optimization of the p-median problem and Swedish population redistribution.   The p-median model is the most representative model in the location analysis. When facilities are located to a population geographically distributed in Q demand points, the p-median model systematically considers all the demand points such that each demand point will have an effect on the decision of the location. However, a series of questions arise. How do we measure the distances? Does the number of facilities to be located have a strong impact on the result? What scale of the network is suitable? How good is our solution? We have scrutinized a lot of issues like those. The reason why we are interested in those questions is that there are a lot of uncertainties in the solutions. We cannot guarantee our solution is good enough for making decisions. The technique of heuristic optimization is formulated in the thesis.   Swedish population redistribution is examined by a spatio-temporal covariance model. A descriptive analysis is not always enough to describe the moving effects from the neighbouring population. A correlation or a covariance analysis is more explicit to show the tendencies. Similarly, the optimization technique of the parameter estimation is required and is executed in the frame of statistical modeling. 

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We studied the distribution of NADPH-diaphorase (NADPH-d) activity in the prefrontal cortex of normal adult Cebus apella monkeys using NADPH-d histochemical protocols. The following regions were studied: granular areas 46 and 12, dysgranular areas 9 and 13, and agranular areas 32 and Oap. NADPH-d-positive neurons were divided into two distinct types, both non-pyramidal. Type I neurons had a large soma diameter (17.24 +/- 1.73 pm) and were densely stained. More than 90% of these neurons were located in the subcortical white matter and infragranular layers. The remaining type I neurons were distributed in the supragranular layers. Type II neurons had a small, round or oval soma (9.83 +/- 1.03 mu m), and their staining pattern varied markedly. Type II neurons were distributed throughout the cortex, with their greatest numerical density being observed in layers II and III. In granular areas, the number of type II neurons was up to 20 times that of type I neurons, but this proportion was smaller in agranular areas. Areal density of type II neurons was maximum in the supragranular layers of granular areas and minimum in agranular areas. Statistical analysis revealed that these areal differences were significant when comparing some specific areas. In conclusion, our results indicate a predominance of NADPH-d-positive cells in supragranular layers of granular areas in the Cebus prefrontal cortex. These findings support previous observations on the role of type II neurons as a new cortical nitric oxide source in supragranular cortical layers in primates, and their potential contribution to cortical neuronal activation in advanced mammals. (c) 2006 Elsevier B.V. All rights reserved.

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

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Several studies suggest that, on a large scale, relief conditions influence the Atlantic Forest cover. The aim of this work was to explore these relationships on a local scale, in Caucaia do Alto, on the Ibiúna Plateau. Within an area of about 78 km2, the distribution of forest cover, divided into two successional stages, was associated with relief attribute data (slope, slope orientation and altitude). The mapping of the vegetation was based on the interpretation of stereoscopic pairs of aerial photographs, from April 2000, on a scale of 1:10,000, while the relief attributes were obtained by geoprocessing from digitalized topographic maps on a scale of 1:10,000. Statistical analyses, based on qui-square tests, revealed that there was a more extensive forest cover, irrespective of the successional stage, in steeper areas (>10 degrees) located at higher altitudes (>923 m), but no influence of the slope orientation. There was no sign of direct influence of relief on the forest cover through environmental gradients that might have contributed to the forest regeneration. Likewise, there was no evidence that these results could have been influenced by the distance from roads or urban areas or with respect to permanent preservation areas. Relief seems to influence the forest cover indirectly, since agricultural land use is preferably made in flatter and lower areas. These results suggest a general distribution pattern of the forest remnants, independent of the scale of study, on which relief indirectly has a strong influence, since it determines human occupation.