913 resultados para Partial Least Squares
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Partition of Unity Implicits (PUI) has been recently introduced for surface reconstruction from point clouds. In this work, we propose a PUI method that employs a set of well-observed solutions in order to produce geometrically pleasant results without requiring time consuming or mathematically overloaded computations. One feature of our technique is the use of multivariate orthogonal polynomials in the least-squares approximation, which allows the recursive refinement of the local fittings in terms of the degree of the polynomial. However, since the use of high-order approximations based only on the number of available points is not reliable, we introduce the concept of coverage domain. In addition, the method relies on the use of an algebraically defined triangulation to handle two important tasks in PUI: the spatial decomposition and an adaptive polygonization. As the spatial subdivision is based on tetrahedra, the generated mesh may present poorly-shaped triangles that are improved in this work by means a specific vertex displacement technique. Furthermore, we also address sharp features and raw data treatment. A further contribution is based on the PUI locality property that leads to an intuitive scheme for improving or repairing the surface by means of editing local functions.
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We report a statistical analysis of Doppler broadening coincidence data of electron-positron annihilation radiation in silicon using a (22)Na source. The Doppler broadening coincidence spectrum was fit using a model function that included positron annihilation at rest with 1s, 2s, 2p, and valence band electrons. In-flight positron annihilation was also fit. The response functions of the detectors accounted for backscattering, combinations of Compton effects, pileup, ballistic deficit, and pulse-shaping problems. The procedure allows the quantitative determination of positron annihilation with core and valence electron intensities as well as their standard deviations directly from the experimental spectrum. The results obtained for the core and valence band electron annihilation intensities were 2.56(9)% and 97.44(9)%, respectively. These intensities are consistent with published experimental data treated by conventional analysis methods. This new procedure has the advantage of allowing one to distinguish additional effects from those associated with the detection system response function. (C) 2009 Elsevier B.V. All rights reserved.
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Mebendazole (MBZ) is a common benzimidazole anthelmintic that exists in three different polymorphic forms, A, B, and C. Polymorph C is the pharmaceutically preferred form due to its adequated aqueous solubility. No single crystal structure determinations depicting the nature of the crystal packing and molecular conformation and geometry have been performed on this compound. The crystal structure of mebendazole form C is resolved for the first time. Mebendazole form C crystallizes in the triclinic centrosymmetric space group and this drug is practically planar, since the least-squares methyl benzimidazolylcarbamate plane is much fitted on the forming atoms. However, the benzoyl group is twisted by 31(1)degrees from the benzimidazole ring, likewise the torsional angle between the benzene and carbonyl moieties is 27(1)degrees. The formerly described bends and other interesting intramolecular geometry features were viewed as consequence of the intermolecular contacts occurring within mebendazole C structure. Among these features, a conjugation decreasing through the imine nitrogen atom of the benzimidazole core and a further resonance path crossing the carbamate one were described. At last, the X-ray powder diffractogram of a form C rich mebendazole mixture was overlaid to the calculated one with the mebendazole crystal structure. (C) 2008 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 98:2336-2344, 2009
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Semi-empirical weighted oscillator strengths (gf) and lifetimes presented in this work for all experimentally known electric dipole P XII spectral lines and energy levels were computed within a multiconfiguration Hartree-Fock relativistic approach. In this calculation, the electrostatic parameters were optimized by a least-squares procedure in order to improve the adjustment to experimental energy levels. The method produces lifetime and gf values that are in agreement with intensity observations used for the interpretation of spectrograms of solar and laboratory plasmas.
Exact penalties for variational inequalities with applications to nonlinear complementarity problems
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In this paper, we present a new reformulation of the KKT system associated to a variational inequality as a semismooth equation. The reformulation is derived from the concept of differentiable exact penalties for nonlinear programming. The best theoretical results are presented for nonlinear complementarity problems, where simple, verifiable, conditions ensure that the penalty is exact. We close the paper with some preliminary computational tests on the use of a semismooth Newton method to solve the equation derived from the new reformulation. We also compare its performance with the Newton method applied to classical reformulations based on the Fischer-Burmeister function and on the minimum. The new reformulation combines the best features of the classical ones, being as easy to solve as the reformulation that uses the Fischer-Burmeister function while requiring as few Newton steps as the one that is based on the minimum.
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This paper derives the second-order biases Of maximum likelihood estimates from a multivariate normal model where the mean vector and the covariance matrix have parameters in common. We show that the second order bias can always be obtained by means of ordinary weighted least-squares regressions. We conduct simulation studies which indicate that the bias correction scheme yields nearly unbiased estimators. (C) 2009 Elsevier B.V. All rights reserved.
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To identify chemical descriptors to distinguish Cuban from non-Cuban rums, analyses of 44 samples of rum from 15 different countries are described. To provide the chemical descriptors, analyses of the the mineral fraction, phenolic compounds, caramel, alcohols, acetic acid, ethyl acetate, ketones, and aldehydes were carried out. The analytical data were treated through the following chemometric methods: principal component analysis (PCA), partial least square-discriminate analysis (PLS-DA), and linear discriminate analysis (LDA). These analyses indicated 23 analytes as relevant chemical descriptors for the separation of rums into two distinct groups. The possibility of clustering the rum samples investigated through PCA analysis led to an accumulative percentage of 70.4% in the first three principal components, and isoamyl alcohol, n-propyl alcohol, copper, iron, 2-furfuraldehyde (furfuraldehyde), phenylmethanal (benzaldehyde), epicatechin, and vanillin were used as chemical descriptors. By applying the PLS-DA technique to the whole set of analytical data, the following analytes have been selected as descriptors: acetone, sec-butyl alcohol, isobutyl alcohol, ethyl acetate, methanol, isoamyl alcohol, magnesium, sodium, lead, iron, manganese, copper, zinc, 4-hydroxy3,5-dimethoxybenzaldehyde (syringaldehyde), methaldehyde (formaldehyde), 5-hydroxymethyl-2furfuraldehyde (5-HMF), acetalclehyde, 2-furfuraldehyde, 2-butenal (crotonaldehyde), n-pentanal (valeraldehyde), iso-pentanal (isovaleraldehyde), benzaldehyde, 2,3-butanodione monoxime, acetylacetone, epicatechin, and vanillin. By applying the LIDA technique, a model was developed, and the following analytes were selected as descriptors: ethyl acetate, sec-butyl alcohol, n-propyl alcohol, n-butyl alcohol, isoamyl alcohol, isobutyl alcohol, caramel, catechin, vanillin, epicatechin, manganese, acetalclehyde, 4-hydroxy-3-methoxybenzoic acid, 2-butenal, 4-hydroxy-3,5-dimethoxybenzoic acid, cyclopentanone, acetone, lead, zinc, calcium, barium, strontium, and sodium. This model allowed the discrimination of Cuban rums from the others with 88.2% accuracy.
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Drinking water distribution networks risk exposure to malicious or accidental contamination. Several levels of responses are conceivable. One of them consists to install a sensor network to monitor the system on real time. Once a contamination has been detected, this is also important to take appropriate counter-measures. In the SMaRT-OnlineWDN project, this relies on modeling to predict both hydraulics and water quality. An online model use makes identification of the contaminant source and simulation of the contaminated area possible. The objective of this paper is to present SMaRT-OnlineWDN experience and research results for hydraulic state estimation with sampling frequency of few minutes. A least squares problem with bound constraints is formulated to adjust demand class coefficient to best fit the observed values at a given time. The criterion is a Huber function to limit the influence of outliers. A Tikhonov regularization is introduced for consideration of prior information on the parameter vector. Then the Levenberg-Marquardt algorithm is applied that use derivative information for limiting the number of iterations. Confidence intervals for the state prediction are also given. The results are presented and discussed on real networks in France and Germany.
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Dissertação apresentada ao Programa de Pós-graduação em Administração da Universidade Municipal de são Caetano do Sul
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The study aims to assess the empirical adherence of the permanent income theory and the consumption smoothing view in Latin America. Two present value models are considered, one describing household behavior and the other open economy macroeconomics. Following the methodology developed in Campbell and Schiller (1987), Bivariate Vector Autoregressions are estimated for the saving ratio and the real growth rate of income concerning the household behavior model and for the current account and the change in national cash ‡ow regarding the open economy model. The countries in the sample are considered separately in the estimation process (individual system estimation) as well as jointly (joint system estimation). Ordinary Least Squares (OLS) and Seemingly Unrelated Regressions (SURE) estimates of the coe¢cients are generated. Wald Tests are then conducted to verify if the VAR coe¢cient estimates are in conformity with those predicted by the theory. While the empirical results are sensitive to the estimation method and discount factors used, there is only weak evidence in favor of the permanent income theory and consumption smoothing view in the group of countries analyzed.
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Estimating the parameters of the instantaneous spot interest rate process is of crucial importance for pricing fixed income derivative securities. This paper presents an estimation for the parameters of the Gaussian interest rate model for pricing fixed income derivatives based on the term structure of volatility. We estimate the term structure of volatility for US treasury rates for the period 1983 - 1995, based on a history of yield curves. We estimate both conditional and first differences term structures of volatility and subsequently estimate the implied parameters of the Gaussian model with non-linear least squares estimation. Results for bond options illustrate the effects of differing parameters in pricing.
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Empirical evidence suggests that real exchange rate is characterized by the presence of near-unity and additive outliers. Recent studeis have found evidence on favor PPP reversion by using the quasi-differencing (Elliott et al., 1996) unit root tests (ERS), which is more efficient against local alternatives but is still based on least squares estimation. Unit root tests basead on least saquares method usually tend to bias inference towards stationarity when additive out liers are present. In this paper, we incorporate quasi-differencing into M-estimation to construct a unit root test that is robust not only against near-unity root but also against nonGaussian behavior provoked by assitive outliers. We re-visit the PPP hypothesis and found less evidemce in favor PPP reversion when non-Gaussian behavior in real exchange rates is taken into account.
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O objetivo desse trabalho é mostrar a importância das instituições orçamentárias quando se estuda o efeito da descentralização sobre o tamanho dos governos subnacionais. No caso do Brasil, observamos que as mudanças institucionais iniciaram-se com a descentralização, oriunda de alterações determinadas pela Nova Constituição Federal de 1988, e que por sua vez possibilitou um conjunto de mudanças que determinou como resultado final a alteração do tamanho dos governos estaduais ao longo do tempo. Embora essas fossem promovidas pelo governo federal, a grande maioria delas aconteceu no sentido de tornar a restrição orçamentária dos governos estaduais mais hard, ou seja, os governos subnacionais teriam cada vez menos canais para ampliar seu endividamento, e com esse limitado, eles teriam que se adequar a uma realidade orçamentária mais rígida, em que as despesas teriam que seguir o comportamento das receitas; se essas crescessem, as despesas poderiam crescer, mas se houvesse uma diminuição, as despesas teriam que ser adequadas a esse novo montante de recurso. Das quatro mudanças nas instituições orçamentárias encontradas na literatura, três delas se mostraram importantes empiricamente na determinação do tamanho dos governos subnacionais: A Nova Constituição implantada em 1988, a mudança na forma de fazer orçamento (Efeito-Bacha) e a Lei de Responsabilidade Fiscal. Os resultados demonstraram que a primeira seguiu na direção de aumentar o tamanho dos governos subnacionais através do aumento de recursos transferidos via Fundo de Participação dos Estados; a segunda provocou uma diminuição no tamanho por impor uma nova realidade orçamentária, em que os governos deveriam trabalhar com o orçamento em termos reais de acordo com o que fosse determinado 6 em termos nominais; com relação à Lei de Responsabilidade Fiscal que apresentou um comportamento no sentido de aumentar o tamanho dos governos, há a questão da falta de observações em número suficiente para que seu resultado seja robusto, contudo já se percebe o sentido da influência que essa mudança teve. No caso da Renegociação das dívidas ocorrida entre os governos estaduais e a União, seu resultado mostrou-se mais como um choque negativo, do que como uma alteração que provocasse uma mudança de nível no tamanho dos governos. Trabalhamos com vinte e seis estados e um Distrito Federal entre os anos de 1986 e 2003 usando o modelo de Least Squares Dummy Variable (LSDV).
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Este trabalho visa investigar o analfabetismo no Brasil a partir do uso de novas medidas de alfabetização inicialmente desenvolvidas por Basu e Foster (1998). Para tanto, primeiro se avalia o perfil de alfabetização da população brasileira de acordo com a definição de analfabetismo isolado. Entende-se por analfabetos isolados aqueles indivíduos analfabetos que não convivem com pessoas alfabetizadas em nível domiciliar. Segundo, busca-se evidências de externalidades domiciliares da alfabetização de filhos em aspectos relacionados a salários e à participação no mercado de trabalho de pais analfabetos. Devido à suspeita de causalidade reversa nas estimações por Mínimos Quadrados Ordinários (MQO) das equações que relacionam as variáveis de interesse dos pais com as alfabetizações dos filhos, utiliza-se as ofertas municipais de escolas e professores de primeiro grau como variáveis instrumentais para a alfabetização. Da investigação do perfil de alfabetização constata-se que a região Nordeste é a que apresenta os piores resultados entre as regiões do país, uma vez que é a que tem a maior parcela de analfabetos isolados do total. Tal resultado condiciona políticas públicas de alfabetização para essa região. As aplicações das medidas indicam que os rankings de alfabetização por estados são sensíveis às diferentes medidas. Os resultados encontrados das estimações por MQO indicam haver correlação positiva entre as variáveis dependentes dos pais e alfabetização dos filhos. Entretanto, a aplicação da metodologia de variáveis instrumentais não confirma os resultados das estimações por MQO. Contudo, devido à fragilidade dos resultados das estimações do primeiro estágio, não se pode afirmar que não há externalidades da alfabetização dos filhos para os pais.
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This dissertation proposes a bivariate markov switching dynamic conditional correlation model for estimating the optimal hedge ratio between spot and futures contracts. It considers the cointegration between series and allows to capture the leverage efect in return equation. The model is applied using daily data of future and spot prices of Bovespa Index and R$/US$ exchange rate. The results in terms of variance reduction and utility show that the bivariate markov switching model outperforms the strategies based ordinary least squares and error correction models.