885 resultados para Asymptotic covariance matrix
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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The objective of the present study was to investigate the effect of data structure on estimated genetic parameters and predicted breeding values of direct and maternal genetic effects for weaning weight (WW) and weight gain from birth to weaning (BWG), including or not the genetic covariance between direct and maternal effects. Records of 97,490 Nellore animals born between 1993 and 2006, from the Jacarezinho cattle raising farm, were used. Two different data sets were analyzed: DI_all, which included all available progenies of dams without their own performance; DII_all, which included DI_all + 20% of recorded progenies with maternal phenotypes. Two subsets were obtained from each data set (DI_all and DII_all): DI_1 and DII_1, which included only dams with three or fewer progenies; DI_5 and DII_5, which included only dams with five or more progenies. (Co)variance components and heritabilities were estimated by Bayesian inference through Gibbs sampling using univariate animal models. In general, for the population and traits studied, the proportion of dams with known phenotypic information and the number of progenies per dam influenced direct and maternal heritabilities, as well as the contribution of maternal permanent environmental variance to phenotypic variance. Only small differences were observed in the genetic and environmental parameters when the genetic covariance between direct and maternal effects was set to zero in the data sets studied. Thus, the inclusion or not of the genetic covariance between direct and maternal effects had little effect on the ranking of animals according to their breeding values for WW and BWG. Accurate estimation of genetic correlations between direct and maternal genetic effects depends on the data structure. Thus, this covariance should be set to zero in Nellore data sets in which the proportion of dams with phenotypic information is low, the number of progenies per dam is small, and pedigree relationships are poorly known. (c) 2012 Elsevier B.V. All rights reserved.
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The portfolio theory is a field of study devoted to investigate the decision-making by investors of resources. The purpose of this process is to reduce risk through diversification and thus guarantee a return. Nevertheless, the classical Mean-Variance has been criticized regarding its parameters and it is observed that the use of variance and covariance has sensitivity to the market and parameter estimation. In order to reduce the estimation errors, the Bayesian models have more flexibility in modeling, capable of insert quantitative and qualitative parameters about the behavior of the market as a way of reducing errors. Observing this, the present study aimed to formulate a new matrix model using Bayesian inference as a way to replace the covariance in the MV model, called MCB - Covariance Bayesian model. To evaluate the model, some hypotheses were analyzed using the method ex post facto and sensitivity analysis. The benchmarks used as reference were: (1) the classical Mean Variance, (2) the Bovespa index's market, and (3) in addition 94 investment funds. The returns earned during the period May 2002 to December 2009 demonstrated the superiority of MCB in relation to the classical model MV and the Bovespa Index, but taking a little more diversifiable risk that the MV. The robust analysis of the model, considering the time horizon, found returns near the Bovespa index, taking less risk than the market. Finally, in relation to the index of Mao, the model showed satisfactory, return and risk, especially in longer maturities. Some considerations were made, as well as suggestions for further work
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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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Markovian algorithms for estimating the global maximum or minimum of real valued functions defined on some domain Omega subset of R-d are presented. Conditions on the search schemes that preserve the asymptotic distribution are derived. Global and local search schemes satisfying these conditions are analysed and shown to yield sharper confidence intervals when compared to the i.i.d. case.
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Adhesion to extracellular matrix (ECM) proteins plays a crucial role in invasive fungal diseases. ECM proteins bind to the surface of Paracoccidioides brasiliensis yeast cells in distinct qualitative patterns. Extracts from Pb18 strain, before (18a) and after animal inoculation (18b), exhibited differential adhesion to ECM components. Pb18b extract had a higher capacity for binding to ECM components than Pb18a. Laminin was the most adherent component for both samples, followed by type I collagen, fibronectin, and type IV collagen for Pb18b. A remarkable difference was seen in the interaction of the two extracts with fibronectin and their fragments. Pb18b extract interacted significantly with the 120-kDa fragment. Ligand affinity binding assays showed that type I collagen recognized two components (47 and 80 kDa) and gp43 bound both fibronectin and laminin. The peptide 1 (NLGRDAKRHL) from gp43, with several positively charged amino acids, contributed most to the adhesion of P. brasiliensis to Vero cells. Synthetic peptides derived from peptide YIGRS of laminin or from RGD of both laminin and fibronectin showed the greatest inhibition of adhesion of gp43 to Vero cells. In conclusion, this work provided new molecular details on the interaction between P. brasiliensis and ECNI components. (c) 2006 Elsevier SAS. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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We present a simple procedure to obtain the maximally localized Wannier function of isolated bands in one-dimensional crystals with or without inversion symmetry. First, we discuss the generality of dealing with real Wannier functions. Next, we use a transfer-matrix technique to obtain nonoptimal Bloch functions which are analytic in the wave number. This produces two classes of real Wannier functions. Then, the minimization of the variance of the Wannier functions is performed, by using the antiderivative of the Berry connection. In the case of centrosymmetric crystals, this procedure leads to the Wannier-Kohn functions. The asymptotic behavior of the Wannier functions is also analyzed. The maximally localized Wannier functions show the expected exponential and power-law decays. Instead, nonoptimal Wannier functions may show reduced exponential and anisotropic power-law decays. The theory is illustrated with numerical calculations of Wannier functions for conduction electrons in semiconductor superlattices.
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In this work we have elaborated a spline-based method of solution of inicial value problems involving ordinary differential equations, with emphasis on linear equations. The method can be seen as an alternative for the traditional solvers such as Runge-Kutta, and avoids root calculations in the linear time invariant case. The method is then applied on a central problem of control theory, namely, the step response problem for linear EDOs with possibly varying coefficients, where root calculations do not apply. We have implemented an efficient algorithm which uses exclusively matrix-vector operations. The working interval (till the settling time) was determined through a calculation of the least stable mode using a modified power method. Several variants of the method have been compared by simulation. For general linear problems with fine grid, the proposed method compares favorably with the Euler method. In the time invariant case, where the alternative is root calculation, we have indications that the proposed method is competitive for equations of sifficiently high order.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)