10 resultados para additive interpolation error expansion

em Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco


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This paper proposes a GARCH-type model allowing for time-varying volatility, skewness and kurtosis. The model is estimated assuming a Gram-Charlier series expansion of the normal density function for the error term, which is easier to estimate than the non-central t distribution proposed by Harvey and Siddique (1999). Moreover, this approach accounts for time-varying skewness and kurtosis while the approach by Harvey and Siddique (1999) only accounts for nonnormal skewness. We apply this method to daily returns of a variety of stock indices and exchange rates. Our results indicate a significant presence of conditional skewness and kurtosis. It is also found that specifications allowing for time-varying skewness and kurtosis outperform specifications with constant third and fourth moments.

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[ES]El objeto de este artículo es saber hasta qué punto pudo emplearse la justicia penal como un instrumento más de la política de carácter antijudío desarrollada por las autoridades cristianas de la España medieval a finales del siglo XV, concretamente en los momentos previos a la expulsión. Para indagar sobre esta cuestión se tendrá presente el proceso penal por blasfemia al que fue sometido el judío de Vitoria (Álava) Jato Tello.

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Este trabajo se encuentra bajo la licencia Creative Commons Attribution 3.0.

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El objeto del presente trabajo, titulado “Aplicación de redes neuronales artificiales para la caracterización del error en trayectorias circulares por WEDM”, es el estudio y posterior optimización del error en trayectorias circulares mecanizadas mediante electroerosión por hilo. Se pretende desarrollar un modelo predictivo de dicho error a través de la implementación de una Red Neuronal Artificial (RNA), que deberá ser alimentada con resultados empíricos resultantes de una batería de ensayos. El modelo desarrollado permitirá conocer a priori los errores que se producirán al cortar formas circulares en distintos espesores y con distintos radios sin necesidad de recurrir a costosas baterías de ensayos.

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Background: The high demanding computational requirements necessary to carry out protein motion simulations make it difficult to obtain information related to protein motion. On the one hand, molecular dynamics simulation requires huge computational resources to achieve satisfactory motion simulations. On the other hand, less accurate procedures such as interpolation methods, do not generate realistic morphs from the kinematic point of view. Analyzing a protein's movement is very similar to serial robots; thus, it is possible to treat the protein chain as a serial mechanism composed of rotational degrees of freedom. Recently, based on this hypothesis, new methodologies have arisen, based on mechanism and robot kinematics, to simulate protein motion. Probabilistic roadmap method, which discretizes the protein configurational space against a scoring function, or the kinetostatic compliance method that minimizes the torques that appear in bonds, aim to simulate protein motion with a reduced computational cost. Results: In this paper a new viewpoint for protein motion simulation, based on mechanism kinematics is presented. The paper describes a set of methodologies, combining different techniques such as structure normalization normalization processes, simulation algorithms and secondary structure detection procedures. The combination of all these procedures allows to obtain kinematic morphs of proteins achieving a very good computational cost-error rate, while maintaining the biological meaning of the obtained structures and the kinematic viability of the obtained motion. Conclusions: The procedure presented in this paper, implements different modules to perform the simulation of the conformational change suffered by a protein when exerting its function. The combination of a main simulation procedure assisted by a secondary structure process, and a side chain orientation strategy, allows to obtain a fast and reliable simulations of protein motion.

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[ES]En la actualidad el proceso de mecanizado mediante electroerosión por hilo (WEDM) posee varias problemáticas a la hora de la ejecución de los cortes para producir diferentes formas, ya sean esquinas, radios de redondeo o de acuerdo y por último la realización de círculos. Es por ello por lo que se elabora el presente trabajo cuya finalidad es llegar a caracterizar los errores cometidos en el corte de desbaste de probetas con trayectorias circulares y tecnología estándar. De esta manera se podrá cuantificar las desviaciones que se producen en las piezas en función del espesor y de sus radios. Toda la información obtenida en el trabajo permitirá una futura actuación en diversos parámetros máquina, elaborando nuevas tecnologías o bien poder mitigarlos realizando correcciones geométricas, ajustando sus tolerancias.

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We review the appropriateness of using SNIa observations to detect potential signatures of anisotropic expansion in the Universe. We focus on Union2 and SNLS3 SNIa datasets and use the hemispherical comparison method to detect possible anisotropic features. Unlike some previous works where nondiagonal elements of the covariance matrix were neglected, we use the full covariance matrix of the SNIa data, thus obtaining more realistic and not underestimated errors. As a matter of fact, the significance of previously claimed detections of a preferred direction in the Union2 dataset completely disappears once we include the effects of using the full covariance matrix. Moreover, we also find that such apreferred direction is aligned with the orthogonal direction of the SDSS observational plane and this suggests a clear indication that the SDSS subsample of the Union2 dataset introduces a significant bias, making the detected preferred direction unphysical. We thus find that current SNIa surveys are inappropriate to test anisotropic features due to their highly non-homogeneous angular distribution in the sky. In addition, after removal of the highest in homogeneous sub-samples, the number of SNIa is too low. Finally, we take advantage of the particular distribution of SNLS SNIa sub- sample in the SNLS3 data set, in which the observations were taken along four different directions. We fit each direction independently and find consistent results at the 1 sigma level. Although the likelihoods peak at relatively different values of Omega(m), the low number of data along each direction gives rise to large errors so that the likelihoods are sufficiently broad as to overlap within 1 sigma. (C) 2014 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http:// creativecommons. org/licenses/by/4.0/).