858 resultados para Robust Statistics
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The data revolution for sustainable development has triggered interest in the use of big data for official statistics such that theUnited Nations Economic and Social Council considers it to be almost an obligation for statistical organizations to explore big data. Big data has been promoted as a more timely and cheaper alternative to traditional sources of official data, and one that offers great potential for monitoring the sustainable development goals. However, privacy concerns, technology and capacity remain significant obstacles to the use of big data. This study makes a case for incorporating big data in official statitics in the Caribbean by highlight the opportunities that big data provides for the subregion, while suggesting ways to manage the challenges. It serves as a starting point for further discussions on the many facets of big data and provides an initial platform upon which a Caribbean big data strategy could be built.
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OBJETIVO: Avaliar a evolução metodológica e do delineamento estatístico nas publicações da Revista Brasileira de Ginecologia e Obstetrícia (RBGO) a partir da resolução 196/96. MÉTODOS: Uma revisão de 133 artigos publicados nos anos de 1999 (65) e 2009 (68) foi realizada por dois revisores independentes com formação em epidemiologia clínica e metodologia da pesquisa científica. Foram incluídos todos os artigos clínicos originais, séries e relatos de casos, sendo excluídos os editoriais, as cartas ao editor, os artigos de revisão sistemática, os trabalhos experimentais, artigos de opinião, além dos resumos de teses e dissertações. Características relacionadas com a qualidade metodológica dos estudos foram analisadas por artigo, por meio de check-list que avaliou dois critérios: aspectos metodológicos e procedimentos estatísticos. Utilizou-se a estatística descritiva e o teste do χ2 para comparação entre os anos. RESULTADOS: Observa-se que houve diferença entre os anos de 1999 e 2009 no tocante ao desenho dos estudos e ao delineamento estatístico, demonstrando maior rigor nos respectivos procedimentos com o uso de testes mais robustos, relativamente, entre os anos de 1999 e 2009. CONCLUSÕES: Na RBGO, observou-se evolução metodológica dos artigos publicados entre os anos de 1999 e 2009 e aprofundamento nas análises estatísticas com o uso de testes mais sofisticados, como o uso mais frequente das análises de regressão e da análise multinível, que são técnicas primordiais na produção do conhecimento e planejamento de intervenções em saúde. Isso pode resultar em menos erros de interpretações.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Statistical methods for analyzing agroecological data might not be able to help agroecologists to solve all of the current problems concerning crop and animal husbandry, but such methods could well help them assess, tackle, and resolve several agroecological issues in a more reliable and accurate manner. Therefore, our goal in this article is to discuss the importance of statistical tools for alternative agronomic approaches, because alternative approaches, such as organic farming, should not only be promoted by encouraging farmers to deploy agroecological techniques, but also by providing agroecologists with robust analyses based on rigorous statistical procedures.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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This work aims viewing weather information, by building isosurfaces enabling enjoy the advantages of three-dimensional geometric models, to communicate the meaning of the data used in a clear and efficient way. The evolving technology of data processing makes possible the interpretation of masses of data increasing, through robust algorithms. In meteorology, in particular, we can benefit from this fact, due to the large amount of data required for analysis and statistics. The manipulation of data, by users from other areas, is facilitated by the choice of algorithm and the tools involved in this work. The project was further developed into distinct modules, increasing their flexibility and reusability for future studies
Robust controller design of a wheelchair mobile via LMI approach to SPR systems with feedback output
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This article discusses the design of robust controller applied to Wheelchair Furniture via Linear Matrix Inequalities (LMI), to obtain Strictly Positive Real (SPR) systems. The contributions of this work were the choice of a mathematical model for wheelchair: mobile with uncertainty about the position of the center of gravity (CG), the decoupling of the kinematic and dynamical systems, linearization of the models, the headquarters building of parametric uncertainties, the proposal of the control loop and control law with a specified decay rate.
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Voltage-controlled spin electronics is crucial for continued progress in information technology. It aims at reduced power consumption, increased integration density and enhanced functionality where non-volatile memory is combined with highspeed logical processing. Promising spintronic device concepts use the electric control of interface and surface magnetization. From the combination of magnetometry, spin-polarized photoemission spectroscopy, symmetry arguments and first-principles calculations, we show that the (0001) surface of magnetoelectric Cr2O3 has a roughness-insensitive, electrically switchable magnetization. Using a ferromagnetic Pd/Co multilayer deposited on the (0001) surface of a Cr2O3 single crystal, we achieve reversible, room-temperature isothermal switching of the exchange-bias field between positive and negative values by reversing the electric field while maintaining a permanent magnetic field. This effect reflects the switching of the bulk antiferromagnetic domain state and the interface magnetization coupled to it. The switchable exchange bias sets in exactly at the bulk Néel temperature.
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This paper proposes three new hybrid mechanisms for the scheduling of grid tasks, which integrate reactive and proactive approaches. They differ by the scheduler used to define the initial schedule of an application and by the scheduler used to reschedule the application. The mechanisms are compared to reactive and proactive mechanisms. Results show that hybrid approach produces performance close to that of the reactive mechanisms, but demanding less migrations.
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In general the term "Lagrangian coherent structure" (LCS) is used to make reference about structures whose properties are similar to a time-dependent analog of stable and unstable manifolds from a hyperbolic fixed point in Hamiltonian systems. Recently, the term LCS was used to describe a different type of structure, whose properties are similar to those of invariant tori in certain classes of two-dimensional incompressible flows. A new kind of LCS was obtained. It consists of barriers, called robust tori that block the trajectories in certain regions of the phase space. We used the Double-Gyre Flow system as the model. In this system, the robust tori play the role of a skeleton for the dynamics and block, horizontally, vortices that come from different parts of the phase space. (C) 2012 Elsevier B.V. All rights reserved.
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This work addresses the solution to the problem of robust model predictive control (MPC) of systems with model uncertainty. The case of zone control of multi-variable stable systems with multiple time delays is considered. The usual approach of dealing with this kind of problem is through the inclusion of non-linear cost constraint in the control problem. The control action is then obtained at each sampling time as the solution to a non-linear programming (NLP) problem that for high-order systems can be computationally expensive. Here, the robust MPC problem is formulated as a linear matrix inequality problem that can be solved in real time with a fraction of the computer effort. The proposed approach is compared with the conventional robust MPC and tested through the simulation of a reactor system of the process industry.
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An extension of some standard likelihood based procedures to heteroscedastic nonlinear regression models under scale mixtures of skew-normal (SMSN) distributions is developed. This novel class of models provides a useful generalization of the heteroscedastic symmetrical nonlinear regression models (Cysneiros et al., 2010), since the random term distributions cover both symmetric as well as asymmetric and heavy-tailed distributions such as skew-t, skew-slash, skew-contaminated normal, among others. A simple EM-type algorithm for iteratively computing maximum likelihood estimates of the parameters is presented and the observed information matrix is derived analytically. In order to examine the performance of the proposed methods, some simulation studies are presented to show the robust aspect of this flexible class against outlying and influential observations and that the maximum likelihood estimates based on the EM-type algorithm do provide good asymptotic properties. Furthermore, local influence measures and the one-step approximations of the estimates in the case-deletion model are obtained. Finally, an illustration of the methodology is given considering a data set previously analyzed under the homoscedastic skew-t nonlinear regression model. (C) 2012 Elsevier B.V. All rights reserved.