84 resultados para Reproducing kernel
Resumo:
This paper presents an analysis of motor vehicle insurance claims relating to vehicle damage and to associated medical expenses. We use univariate severity distributions estimated with parametric and non-parametric methods. The methods are implemented using the statistical package R. Parametric analysis is limited to estimation of normal and lognormal distributions for each of the two claim types. The nonparametric analysis presented involves kernel density estimation. We illustrate the benefits of applying transformations to data prior to employing kernel based methods. We use a log-transformation and an optimal transformation amongst a class of transformations that produces symmetry in the data. The central aim of this paper is to provide educators with material that can be used in the classroom to teach statistical estimation methods, goodness of fit analysis and importantly statistical computing in the context of insurance and risk management. To this end, we have included in the Appendix of this paper all the R code that has been used in the analysis so that readers, both students and educators, can fully explore the techniques described
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A parts based model is a parametrization of an object class using a collection of landmarks following the object structure. The matching of parts based models is one of the problems where pairwise Conditional Random Fields have been successfully applied. The main reason of their effectiveness is tractable inference and learning due to the simplicity of involved graphs, usually trees. However, these models do not consider possible patterns of statistics among sets of landmarks, and thus they sufffer from using too myopic information. To overcome this limitation, we propoese a novel structure based on a hierarchical Conditional Random Fields, which we explain in the first part of this memory. We build a hierarchy of combinations of landmarks, where matching is performed taking into account the whole hierarchy. To preserve tractable inference we effectively sample the label set. We test our method on facial feature selection and human pose estimation on two challenging datasets: Buffy and MultiPIE. In the second part of this memory, we present a novel approach to multiple kernel combination that relies on stacked classification. This method can be used to evaluate the landmarks of the parts-based model approach. Our method is based on combining responses of a set of independent classifiers for each individual kernel. Unlike earlier approaches that linearly combine kernel responses, our approach uses them as inputs to another set of classifiers. We will show that we outperform state-of-the-art methods on most of the standard benchmark datasets.
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For a quasilinear operator on the semiaxis a reduction theorem is proved on the cones of monotone functions in Lp - Lq setting for 0 < q < ∞, 1<= p < ∞. The case 0 < p < 1 is also studied for operators with additional properties. In particular, we obtain critera for three-weight inequalities for the Hardy-type operators with Oinarov' kernel on monotone functions in the case 0 < q < p <= 1.
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L'objectiu del TFC és crear una 'suite' que resolgui tota la línia de producció d'un podcast. És a dir: captura d'un senyal d'audio en directe, transcodificació, classificació,emmagatzematge i, per acabar, difusió per Internet.
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Aquest projecte es basa en la modificació del kernel (nucli) del sistema operatiu GNU/Linux per dotar-lo de la capacitat d'extreure estadístiques de les crides al sistema (syscalls). A partir de la compilació i instal·lació d'un nou nucli es registra la informació del nombre de vegades i la freqüència amb què es fan aquestes crides al sistema, i posteriorment es representa en un informe d'estadístiques explicatives.
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El projecte que es presenta a continuació és una planificació de migració de servidors físics a un entorn virtualitzat, allà on sigui possible. A més s'ha plantejat una renovació tecnològica de tot el parc de servidors per estalviar diners en el manteniment i en el consum d'energia.La solució de virtualització es buscarà que sigui programari lliure.
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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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A problem in the archaeometric classification of Catalan Renaissance pottery is the fact, thatthe clay supply of the pottery workshops was centrally organized by guilds, and thereforeusually all potters of a single production centre produced chemically similar ceramics.However, analysing the glazes of the ware usually a large number of inclusions in the glaze isfound, which reveal technological differences between single workshops. These inclusionshave been used by the potters in order to opacify the transparent glaze and to achieve a whitebackground for further decoration.In order to distinguish different technological preparation procedures of the single workshops,at a Scanning Electron Microscope the chemical composition of those inclusions as well astheir size in the two-dimensional cut is recorded. Based on the latter, a frequency distributionof the apparent diameters is estimated for each sample and type of inclusion.Following an approach by S.D. Wicksell (1925), it is principally possible to transform thedistributions of the apparent 2D-diameters back to those of the true three-dimensional bodies.The applicability of this approach and its practical problems are examined using differentways of kernel density estimation and Monte-Carlo tests of the methodology. Finally, it istested in how far the obtained frequency distributions can be used to classify the pottery
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A Menorca la tortuga mediterrànea Testudo hermanni és una espècie comuna que es distribueix per quasi tota l'illa. Els estudis anteriors sobre la seva distribució van ser realitzats entre els anys 1970 i 1994. Entre 2003 i 2006 es va prospectar la major part de Menorca amb la finalitat de determinar-ne la distribució actual. A partir de 3647 observacions d'exemplars, se'n va seleccionar aleatòriament una per quadrícula UTM de 0,5 x 0,5 km prospectada. Mitjançant una anàlisi kernel es va calcular que la seva distribució ocupava una superfície de 469 km2 (incloent-hi hàbitats no emprats per les tortugues, com ara zones urbanes o algunes zones boscoses). Aquesta distribució no és continua al llarg de l'illa, sinó que es formada per una sèrie de poblacions més o menys fragmentades i aïllades. D'altra banda, la distribució obtinguda coincideix amb la senyalada en treballs anteriors, la qual cosa s'interpreta com que no hi ha hagut canvis importants en la seva ocupació en els últims deu anys.
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La herramienta de monitorización de clusters MoniTo debe estar preparada ante los constantes cambios en el kernel de Linux que la pudieran dejar inutilizable. Para evitarlo se ha modificado su implementación utilizando librerías Libgtop. También se ha modificado su interfaz web para adaptarla a los nuevos tiempos, optimizar su funcionamiento y dotarla de nuevas posibilidades.
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Dissenyar i implementar un planificador en l'espai d'usuari basant-se en la tècnica de coscheduling, en concret s'utilitzarà coscheduling predictive. L'objectiu és intentar obtenir un rendiment similar al que es va assolir en implementacions de la mateixa tècnica realitzada en l'espai de kernel.
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The front speed of the Neolithic (farmer) spread in Europe decreased as it reached Northern latitudes, where the Mesolithic (huntergatherer) population density was higher. Here, we describe a reaction diffusion model with (i) an anisotropic dispersion kernel depending on the Mesolithicpopulation density gradient and (ii) a modified population growth equation. Both effects are related to the space available for the Neolithic population. The model is able to explain the slowdown of the Neolithic front as observed from archaeological data
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Most integrodifference models of biological invasions are based on the nonoverlapping-generations approximation. However, the effect of multiple reproduction events overlapping generations on the front speed can be very important especially for species with a long life spam . Only in one-dimensional space has this approximation been relaxed previously, although almost all biological invasions take place in two dimensions. Here we present a model that takes into account the overlapping generations effect or, more generally, the stage structure of the population , and we analyze the main differences with the corresponding nonoverlappinggenerations results
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Bimodal dispersal probability distributions with characteristic distances differing by several orders of magnitude have been derived and favorably compared to observations by Nathan [Nature (London) 418, 409 (2002)]. For such bimodal kernels, we show that two-dimensional molecular dynamics computer simulations are unable to yield accurate front speeds. Analytically, the usual continuous-space random walks (CSRWs) are applied to two dimensions. We also introduce discrete-space random walks and use them to check the CSRW results (because of the inefficiency of the numerical simulations). The physical results reported are shown to predict front speeds high enough to possibly explain Reid's paradox of rapid tree migration. We also show that, for a time-ordered evolution equation, fronts are always slower in two dimensions than in one dimension and that this difference is important both for unimodal and for bimodal kernels
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Background: We present the results of EGASP, a community experiment to assess the state-ofthe-art in genome annotation within the ENCODE regions, which span 1% of the human genomesequence. The experiment had two major goals: the assessment of the accuracy of computationalmethods to predict protein coding genes; and the overall assessment of the completeness of thecurrent human genome annotations as represented in the ENCODE regions. For thecomputational prediction assessment, eighteen groups contributed gene predictions. Weevaluated these submissions against each other based on a ‘reference set’ of annotationsgenerated as part of the GENCODE project. These annotations were not available to theprediction groups prior to the submission deadline, so that their predictions were blind and anexternal advisory committee could perform a fair assessment.Results: The best methods had at least one gene transcript correctly predicted for close to 70%of the annotated genes. Nevertheless, the multiple transcript accuracy, taking into accountalternative splicing, reached only approximately 40% to 50% accuracy. At the coding nucleotidelevel, the best programs reached an accuracy of 90% in both sensitivity and specificity. Programsrelying on mRNA and protein sequences were the most accurate in reproducing the manuallycurated annotations. Experimental validation shows that only a very small percentage (3.2%) of the selected 221 computationally predicted exons outside of the existing annotation could beverified.Conclusions: This is the first such experiment in human DNA, and we have followed thestandards established in a similar experiment, GASP1, in Drosophila melanogaster. We believe theresults presented here contribute to the value of ongoing large-scale annotation projects and shouldguide further experimental methods when being scaled up to the entire human genome sequence.