20 resultados para Linear programming models

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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In this paper we obtain asymptotic expansions, up to order n(-1/2) and under a sequence of Pitman alternatives, for the nonnull distribution functions of the likelihood ratio, Wald, score and gradient test statistics in the class of symmetric linear regression models. This is a wide class of models which encompasses the t model and several other symmetric distributions with longer-than normal tails. The asymptotic distributions of all four statistics are obtained for testing a subset of regression parameters. Furthermore, in order to compare the finite-sample performance of these tests in this class of models, Monte Carlo simulations are presented. An empirical application to a real data set is considered for illustrative purposes. (C) 2011 Elsevier B.V. All rights reserved.

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We introduce a new Integer Linear Programming (ILP) approach for solving Integer Programming (IP) problems with bilinear objectives and linear constraints. The approach relies on a series of ILP approximations of the bilinear P. We compare this approach with standard linearization techniques on random instances and a set of real-world product bundling problems. (C) 2011 Elsevier B.V. All rights reserved.

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We consider modifications of the nonlinear Schrodinger model (NLS) to look at the recently introduced concept of quasi-integrability. We show that such models possess an in finite number of quasi-conserved charges which present intriguing properties in relation to very specific space-time parity transformations. For the case of two-soliton solutions where the fields are eigenstates of this parity, those charges are asymptotically conserved in the scattering process of the solitons. Even though the charges vary in time their values in the far past and the far future are the same. Such results are obtained through analytical and numerical methods, and employ adaptations of algebraic techniques used in integrable field theories. Our findings may have important consequences on the applications of these models in several areas of non-linear science. We make a detailed numerical study of the modified NLS potential of the form V similar to (vertical bar psi vertical bar(2))(2+epsilon), with epsilon being a perturbation parameter. We perform numerical simulations of the scattering of solitons for this model and find a good agreement with the results predicted by the analytical considerations. Our paper shows that the quasi-integrability concepts recently proposed in the context of modifications of the sine-Gordon model remain valid for perturbations of the NLS model.

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Setup operations are significant in some production environments. It is mandatory that their production plans consider some features, as setup state conservation across periods through setup carryover and crossover. The modelling of setup crossover allows more flexible decisions and is essential for problems with long setup times. This paper proposes two models for the capacitated lot-sizing problem with backlogging and setup carryover and crossover. The first is in line with other models from the literature, whereas the second considers a disaggregated setup variable, which tracks the starting and completion times of the setup operation. This innovative approach permits a more compact formulation. Computational results show that the proposed models have outperformed other state-of-the-art formulation.

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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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Lemonte and Cordeiro [Birnbaum-Saunders nonlinear regression models, Comput. Stat. Data Anal. 53 (2009), pp. 4441-4452] introduced a class of Birnbaum-Saunders (BS) nonlinear regression models potentially useful in lifetime data analysis. We give a general matrix Bartlett correction formula to improve the likelihood ratio (LR) tests in these models. The formula is simple enough to be used analytically to obtain several closed-form expressions in special cases. Our results generalize those in Lemonte et al. [Improved likelihood inference in Birnbaum-Saunders regressions, Comput. Stat. DataAnal. 54 (2010), pp. 1307-1316], which hold only for the BS linear regression models. We consider Monte Carlo simulations to show that the corrected tests work better than the usual LR tests.

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The choice of an appropriate family of linear models for the analysis of longitudinal data is often a matter of concern for practitioners. To attenuate such difficulties, we discuss some issues that emerge when analyzing this type of data via a practical example involving pretestposttest longitudinal data. In particular, we consider log-normal linear mixed models (LNLMM), generalized linear mixed models (GLMM), and models based on generalized estimating equations (GEE). We show how some special features of the data, like a nonconstant coefficient of variation, may be handled in the three approaches and evaluate their performance with respect to the magnitude of standard errors of interpretable and comparable parameters. We also show how different diagnostic tools may be employed to identify outliers and comment on available software. We conclude by noting that the results are similar, but that GEE-based models may be preferable when the goal is to compare the marginal expected responses.

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In this paper we extend semiparametric mixed linear models with normal errors to elliptical errors in order to permit distributions with heavier and lighter tails than the normal ones. Penalized likelihood equations are applied to derive the maximum penalized likelihood estimates (MPLEs) which appear to be robust against outlying observations in the sense of the Mahalanobis distance. A reweighed iterative process based on the back-fitting method is proposed for the parameter estimation and the local influence curvatures are derived under some usual perturbation schemes to study the sensitivity of the MPLEs. Two motivating examples preliminarily analyzed under normal errors are reanalyzed considering some appropriate elliptical errors. The local influence approach is used to compare the sensitivity of the model estimates.

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We used body mass index (BMI) and waist circumference (WC) as fat indicators to assess whether perinatal and early adulthood factors are associated with adiposity in early adulthood. We hypothesized that risk factors differ between men and women and are also different when WC is used for measuring adiposity as opposed to BMI. We conducted a longitudinal study based on a sample of 2,063 adults from the 1978/1979 Ribeirao Preto birth cohort. Adjustment was performed using four sequential multiple linear regression models stratified by sex. Both perinatal and early adulthood variables influenced adulthood BMI and WC. The associations differed between men and women and depending on the measure of abdominal adiposity (BMI or WC). Living with a partner, for both men and women, and high fat and alcohol intake in men were factors that were consistently associated with higher adulthood BMI and WC levels. The differences observed between sexes may point to different lifestyles of men and women, suggesting that prevention policies should consider gender specific strategies.

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Background: Even though air pollutants exposure is associated with changes in the ocular surface and tear film, its relationship to the clinical course of blepharitis, a common eyelid disease, had not yet been investigated. Our objective was to investigate the correlation between air pollution and acute manifestations of blepharitis. Method: We recorded all cases of changes in the eyelids and ocular surface, and rated clinical findings on a scale from zero (normal) to two (severe alterations). Daily values of carbon monoxide, particulate matter smaller than 10 mu m in diameter and nitrogen dioxide concentrations and meteorological variables (temperature and relative humidity) in the vicinity of the medical service were obtained. Specific linear regression models for each outcome were constructed including pollutants as independent variables (single pollutant models). Temperature and humidity were included as confounding variables. Results: increases of 28.8 mu g/m(3) in the concentration of particulate matter and 1.1 ppm in the concentration of CO were associated with increases in cases of blepharitis on the day of exposure (5 cases, 95% CI: 1-10 and 6 cases, 95% CI: 1-12, respectively). Conclusion: Exposure to usual air pollutants concentrations present in large cities affects, in a consistent manner, the eyes of residents contributing to the increasing incidence of diseases of the eyelid margin. (C) 2011 Elsevier Inc. All rights reserved.

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The objective of this work was to develop and validate linear regression models to estimate the production of dry matter by Tanzania grass (Megathyrsus maximus, cultivar Tanzania) as a function of agrometeorological variables. For this purpose, data on the growth of this forage grass from 2000 to 2005, under dry-field conditions in Sao Carlos, SP, Brazil, were correlated to the following climatic parameters: minimum and mean temperatures, degree-days, and potential and actual evapotranspiration. Simple linear regressions were performed between agrometeorological variables (independent) and the dry matter accumulation rate (dependent). The estimates were validated with independent data obtained in Sao Carlos and Piracicaba, SP, Brazil. The best statistical results in the development and validation of the models were obtained with the agrometeorological parameters that consider thermal and water availability effects together, such as actual evapotranspiration, accumulation of degree-days corrected by water availability, and the climatic growth index, based on average temperature, solar radiation, and water availability. These variables can be used in simulations and models to predict the production of Tanzania grass.

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The main goal of this article is to consider influence assessment in models with error-prone observations and variances of the measurement errors changing across observations. The techniques enable to identify potential influential elements and also to quantify the effects of perturbations in these elements on some results of interest. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease.

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Objective: To estimate the frequency of anaemia in pregnant women before and after the fortification of flours with Fe. Design: Retrospective study developed from secondary data obtained from medical records. Setting: Two health units in Rio de Janeiro, Brazil. Subjects: Socio-economic, demographic, obstetric and Hb concentration data were collected of 778 pregnant women attending prenatal care. Two study groups were created: the first referred to the period before fortification (G1, n 391), including women whose parturition happened before June 2004; and the second referred to the period after fortification (G2, n 387), including women whose last menstrual cycle happened after June 2005. The Hb cut-off point adopted for anaemia diagnosis was <11.0 g/dl. Results: In linear regression models, when Hb concentration was expressed as a dependent variable, women in G2 presented Hb concentration 0.26 g/dl and 0.36 g/dl higher during the second and third trimesters of pregnancy, respectively, compared with G1. In logistic regression models where the dependent variable was anaemia during the second and third trimesters, it was verified that being a member of G2 was a protective factor against anaemia in the third trimester. Regarding the presence of anaemia at any gestational moment, it was verified that being a member of G2 represented a protective factor against anaemia during pregnancy. Conclusions: Results indicate the protective effect of the fortification of flours with Fe in the fight against gestational anaemia, contributing to prevention and control of this nutritional disorder among pregnant women.

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This study aimed to evaluate the relationship between the cost and energy density of diet consumed in Brazilian households. Data from the Brazilian Household Budget Survey (POF 200812009) were used to identify the main foods and their prices. Similar items were grouped, resulting in a basket of 67 products. Linear programming was applied for the composition of isoenergetic baskets, minimizing the deviation from the average household diet. Restrictions were imposed on the inclusion of items and the energy contribution of the various food groups. A reduction in average cost of diet was applied at intervals of R$0.15 to the lowest possible cost. We identified an inverse association between energy density and cost of diet (p < 0.05), and at the lowest possible cost we obtained the maximum value of energy density Restrictions on the diet's cost resulted in the selection of diets with higher energy density, indicating that cost of diet may lead to the adoption of inadequate diets in Brazil.

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Background: Several parameters are associated with high bone mineral density (BMD), such as overweight, black background, intense physical activity (PA), greater calcium intake and some medications. The objectives are to evaluate the prevalence and the main aspects associated with high BMD in healthy women. Methods: After reviewing the database of approximately 21,500 BMD scans performed in the metropolitan area of Sao Paulo, Brazil, from June 2005 to October 2010, high BMD (over 1400 g/cm(2) at lumbar spine and/or above 1200 g/cm2 at femoral neck) was found in 421 exams. Exclusion criteria were age below 30 or above 60 years, black ethnicity, pregnant or obese women, disease and/or medications known to interfere with bone metabolism. A total of 40 women with high BMD were included and matched with 40 healthy women with normal BMD, paired to weight, age, skin color and menopausal status. Medical history, food intake and PA were assessed through validated questionnaires. Body composition was evaluated through a GE-Lunar DPX MD + bone densitometer. Radiography of the thoracic and lumbar spine was carried out to exclude degenerative alterations or fractures. Biochemical parameters included both lipid and hormonal profiles, along with mineral and bone metabolism. Statistical analysis included parametric and nonparametric tests and linear regression models. P < 0.05 was considered significant. Results: The mean age was 50.9 (8.3) years. There was no significant difference between groups in relation to PA, smoking, intake of calcium and vitamin D, as well as laboratory tests, except serum C-telopeptide of type I collagen (s-CTX), which was lower in the high BMD group (p = 0.04). In the final model of multivariate regression, a lower fat intake and body fatness as well a better profile of LDL-cholesterol predicted almost 35% of high BMD in women. (adjusted R2 = 0.347; p < 0.001). In addition, greater amounts of lean mass and higher IGF-1 serum concentrations played a protective role, regardless age and weight. Conclusion: Our results demonstrate the potential deleterious effect of lipid metabolism-related components, including fat intake and body fatness and worse lipid profile, on bone mass and metabolism in healthy women.