203 resultados para Bayesian hierarchical model

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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Over the years, crop insurance programs became the focus of agricultural policy in the USA, Spain, Mexico, and more recently in Brazil. Given the increasing interest in insurance, accurate calculation of the premium rate is of great importance. We address the crop-yield distribution issue and its implications in pricing an insurance contract considering the dynamic structure of the data and incorporating the spatial correlation in the Hierarchical Bayesian framework. Results show that empirical (insurers) rates are higher in low risk areas and lower in high risk areas. Such methodological improvement is primarily important in situations of limited data.

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In this paper, we compare the performance of two statistical approaches for the analysis of data obtained from the social research area. In the first approach, we use normal models with joint regression modelling for the mean and for the variance heterogeneity. In the second approach, we use hierarchical models. In the first case, individual and social variables are included in the regression modelling for the mean and for the variance, as explanatory variables, while in the second case, the variance at level 1 of the hierarchical model depends on the individuals (age of the individuals), and in the level 2 of the hierarchical model, the variance is assumed to change according to socioeconomic stratum. Applying these methodologies, we analyze a Colombian tallness data set to find differences that can be explained by socioeconomic conditions. We also present some theoretical and empirical results concerning the two models. From this comparative study, we conclude that it is better to jointly modelling the mean and variance heterogeneity in all cases. We also observe that the convergence of the Gibbs sampling chain used in the Markov Chain Monte Carlo method for the jointly modeling the mean and variance heterogeneity is quickly achieved.

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This work aims to compare different nonlinear functions for describing the growth curves of Nelore females. The growth curve parameters, their (co) variance components, and environmental and genetic effects were estimated jointly through a Bayesian hierarchical model. In the first stage of the hierarchy, 4 nonlinear functions were compared: Brody, Von Bertalanffy, Gompertz, and logistic. The analyses were carried out using 3 different data sets to check goodness of fit while having animals with few records. Three different assumptions about SD of fitting errors were considered: constancy throughout the trajectory, linear increasing until 3 yr of age and constancy thereafter, and variation following the nonlinear function applied in the first stage of the hierarchy. Comparisons of the overall goodness of fit were based on Akaike information criterion, the Bayesian information criterion, and the deviance information criterion. Goodness of fit at different points of the growth curve was compared applying the Gelfand`s check function. The posterior means of adult BW ranged from 531.78 to 586.89 kg. Greater estimates of adult BW were observed when the fitting error variance was considered constant along the trajectory. The models were not suitable to describe the SD of fitting errors at the beginning of the growth curve. All functions provided less accurate predictions at the beginning of growth, and predictions were more accurate after 48 mo of age. The prediction of adult BW using nonlinear functions can be accurate when growth curve parameters and their (co) variance components are estimated jointly. The hierarchical model used in the present study can be applied to the prediction of mature BW in herds in which a portion of the animals are culled before adult age. Gompertz, Von Bertalanffy, and Brody functions were adequate to establish mean growth patterns and to predict the adult BW of Nelore females. The Brody model was more accurate in predicting the birth weight of these animals and presented the best overall goodness of fit.

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A continuous version of the hierarchical spherical model at dimension d=4 is investigated. Two limit distributions of the block spin variable X(gamma), normalized with exponents gamma = d + 2 and gamma=d at and above the critical temperature, are established. These results are proven by solving certain evolution equations corresponding to the renormalization group (RG) transformation of the O(N) hierarchical spin model of block size L(d) in the limit L down arrow 1 and N ->infinity. Starting far away from the stationary Gaussian fixed point the trajectories of these dynamical system pass through two different regimes with distinguishable crossover behavior. An interpretation of this trajectories is given by the geometric theory of functions which describe precisely the motion of the Lee-Yang zeroes. The large-N limit of RG transformation with L(d) fixed equal to 2, at the criticality, has recently been investigated in both weak and strong (coupling) regimes by Watanabe (J. Stat. Phys. 115:1669-1713, 2004) . Although our analysis deals only with N = infinity case, it complements various aspects of that work.

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Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is interest in studying latent variables. These latent variables are directly considered in the Item Response Models (IRM) and they are usually called latent traits. A usual assumption for parameter estimation of the IRM, considering one group of examinees, is to assume that the latent traits are random variables which follow a standard normal distribution. However, many works suggest that this assumption does not apply in many cases. Furthermore, when this assumption does not hold, the parameter estimates tend to be biased and misleading inference can be obtained. Therefore, it is important to model the distribution of the latent traits properly. In this paper we present an alternative latent traits modeling based on the so-called skew-normal distribution; see Genton (2004). We used the centred parameterization, which was proposed by Azzalini (1985). This approach ensures the model identifiability as pointed out by Azevedo et al. (2009b). Also, a Metropolis Hastings within Gibbs sampling (MHWGS) algorithm was built for parameter estimation by using an augmented data approach. A simulation study was performed in order to assess the parameter recovery in the proposed model and the estimation method, and the effect of the asymmetry level of the latent traits distribution on the parameter estimation. Also, a comparison of our approach with other estimation methods (which consider the assumption of symmetric normality for the latent traits distribution) was considered. The results indicated that our proposed algorithm recovers properly all parameters. Specifically, the greater the asymmetry level, the better the performance of our approach compared with other approaches, mainly in the presence of small sample sizes (number of examinees). Furthermore, we analyzed a real data set which presents indication of asymmetry concerning the latent traits distribution. The results obtained by using our approach confirmed the presence of strong negative asymmetry of the latent traits distribution. (C) 2010 Elsevier B.V. All rights reserved.

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In this paper, we present a Bayesian approach for estimation in the skew-normal calibration model, as well as the conditional posterior distributions which are useful for implementing the Gibbs sampler. Data transformation is thus avoided by using the methodology proposed. Model fitting is implemented by proposing the asymmetric deviance information criterion, ADIC, a modification of the ordinary DIC. We also report an application of the model studied by using a real data set, related to the relationship between the resistance and the elasticity of a sample of concrete beams. Copyright (C) 2008 John Wiley & Sons, Ltd.

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This paper analyses the presence of financial constraint in the investment decisions of 367 Brazilian firms from 1997 to 2004, using a Bayesian econometric model with group-varying parameters. The motivation for this paper is the use of clustering techniques to group firms in a totally endogenous form. In order to classify the firms we used a hybrid clustering method, that is, hierarchical and non-hierarchical clustering techniques jointly. To estimate the parameters a Bayesian approach was considered. Prior distributions were assumed for the parameters, classifying the model in random or fixed effects. Ordinate predictive density criterion was used to select the model providing a better prediction. We tested thirty models and the better prediction considers the presence of 2 groups in the sample, assuming the fixed effect model with a Student t distribution with 20 degrees of freedom for the error. The results indicate robustness in the identification of financial constraint when the firms are classified by the clustering techniques. (C) 2010 Elsevier B.V. All rights reserved.

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This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.

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OBJETIVO: Analisar a associação do sobrepeso e da obesidade com o aleitamento materno e a alimentação complementar em pré-escolares. MÉTODOS: Estudo transversal envolvendo 566 crianças matriculadas em escolas particulares no município de São Paulo, SP, 2004-2005. A variável dependente foi sobrepeso e obesidade. Para a classificação do estado nutricional das crianças foram utilizadas as curvas de percentis do Índice de Massa Corporal para idade, classificando como sobrepeso valores e"P85 e modelo hierarquizado. RESULTADOS: A prevalência de sobrepeso e obesidade da população estudada foi de 34,4%. Foram fatores de proteção contra sobrepeso e obesidade o aleitamento materno exclusivo por seis meses ou mais (IC 95% [0,38;0,86]; OR=0,57; p=0,02) e o aleitamento materno por mais de 24 meses (IC 95% [0,05;0,37]; OR=0,13; p=0,00). CONCLUSÕES: Os resultados sugerem que o aleitamento materno pode proteger as crianças contra o sobrepeso e a obesidade, agregando mais uma vantagem ao leite materno.

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Estudo transversal de base populacional que investigou prevalênciasde anemia e fatores associados à anemia, anemia ferropriva e deficiência de ferro entre crianças de 6 a 60 meses da área urbana de dois municípios do Acre, Brasil (N = 624). Dosagens de hemoglobina sanguínea, ferritina e receptor solúvel de transferrina plasmáticas foram realizadas mediante sangue venoso. Condições sócio-econômicas, demográficas e de morbidade foram obtidas por questionário. Razões de prevalências foram calculadas por regressão de Poisson em modelo hierárquico. As prevalências de anemia, anemia ferropriva e deficiência de ferro foram de 30,6%, 20,9% e 43,5%, respectivamente. Menores de 24 meses apresentaram maior risco para anemia, anemia ferropriva e deficiência de ferro. Pertencer ao maior tercil do índice de riqueza conferiu proteção contra anemia ferropriva (RP = 0,62; IC95%: 0,40-0,98). Pertencer ao maior quartil do índice estatura/idade foi protetor contra anemia (0,62; 0,44-0,86) e anemia ferropriva (0,51; 0,33-0,79), e ocorrência recente de diarréia representou risco (anemia: 1,47; 1,12-1,92 e anemia ferropriva: 1,44; 1,03-2,01). A infestação por geohelmintos conferiu risco para anemia, anemia ferropriva e deficiência de ferro.

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Background: To estimate the prevalence of and identify factors associated with physical activity in leisure, transportation, occupational, and household settings. Methods: This was a cross-sectional study aimed at investigating living and health conditions among the population of São Paulo, Brazil. Data on 1318 adults aged 18 to 65 years were used. To assess physical activity, the long version of the International Physical Activity Questionnaire was applied. Multivariate analysis was conducted using a hierarchical model. Results: The greatest prevalence of insufficient activity related to transportation (91.7%), followed by leisure (77.5%), occupational (68.9%), and household settings (56.7%). The variables associated with insufficient levels of physical activity in leisure were female sex, older age, low education level, nonwhite skin color, smoking, and self-reported poor health; in occupational settings were female sex, white skin color, high education level, self-reported poor health, nonsmoking, and obesity; in transportation settings were female sex; and in household settings, with male sex, separated, or widowed status and high education level. Conclusion: Physical activity in transportation and leisure settings should be encouraged. This study will serve as a reference point in monitoring different types of physical activities and implementing public physical activity policies in developing countries

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OBJETIVO: Descrever a prevalência e analisar fatores associados ao retardo estatural em menores de cinco anos. MÉTODOS: Estudo “baseline”, que analisou 2.040 menores de cinco anos, verificando possíveis associações entre o retardo estatural (índice altura/idade ≤ 2 escores Z) e variáveis hierarquizadas em seis blocos: socioeconômicas, do domicílio, do saneamento, maternas, biológicas e de acesso aos serviços de saúde. A análise multivariada foi realizada por regressão de Poisson, com opção de erro padrão robusto, obtendo-se as razões de prevalência ajustadas, com IC 95por cento e respectivos valores de significância. RESULTADOS: Entre as variáveis não dicotômicas, houve associação positiva com tipo de teto e número de moradores por cômodo e associação negativa com renda, escolaridade da mãe e peso ao nascer. A análise ajustada indicou ainda como variáveis significantes: abastecimento de água, visita do agente comunitário de saúde, local do parto, internação por diarréia e internação por pneumonia. CONCLUSÃO: Os fatores identificados como de risco para o retardo estatural configuram a multicausalidade do problema, implicando na necessidade de intervenções multisetoriais e multiníveis para o seu controle

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Background: To estimate the prevalence of and identify factors associated with physical activity in leisure, transportation, occupational, and household settings. Methods: This was a cross-sectional study aimed at investigating living and health conditions among the population of So Paulo, Brazil. Data on 1318 adults aged 18 to 65 years were used. To assess physical activity, the long version of the International Physical Activity Questionnaire was applied. Multivariate analysis was conducted using a hierarchical model. Results: The greatest prevalence of insufficient activity related to transportation (91.7%), followed by leisure (77.5%), occupational (68.9%), and household settings (56.7%). The variables associated with insufficient levels of physical activity in leisure were female sex, older age, low education level, nonwhite skin color, smoking, and self-reported poor health; in occupational settings were female sex, white skin color, high education level, self-reported poor health, nonsmoking, and obesity; in transportation settings were female sex; and in household settings, with male sex, separated, or widowed status and high education level. Conclusion: Physical activity in transportation and leisure settings should be encouraged. This study will serve as a reference point in monitoring different types of physical activities and implementing public physical activity policies in developing countries.

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Background A higher burden of head and neck cancer has been reported to affect deprived populations. This study assessed the association between socioeconomic status and head and neck cancer, aiming to explore how this association is related to differences of tobacco and alcohol consumption across socioeconomic strata. Methods We conducted a case-control study in Sao Paulo, Brazil (1998-2006), including 1017 incident cases of oral, pharyngeal and laryngeal cancer, and 951 sex- and age-matched controls. Education and occupation were distal determinants in the hierarchical approach; cumulative exposure to tobacco and alcohol were proximal risk factors. Outcomes of the hierarchical model were compared with fully adjusted ORs. Results Individuals with lower education (OR 2.27; 95% CI 1.61 to 3.19) and those performing manual labour (OR 1.55; 95% CI 1.26 to 1.92) had a higher risk of disease. However, 54% of the association with lower education and 45% of the association with manual labour were explained by proximal lifestyle exposures, and socioeconomic status remained significantly associated with disease when adjusted for smoking and alcohol consumption. Conclusions Socioeconomic differences in head and neck cancer are partially attributable to the distribution of tobacco smoking and alcohol consumption across socioeconomic strata. Additional mediating factors may explain the remaining variation of socioeconomic status on head and neck cancer.

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The present paper proposes a flexible consensus scheme for group decision making, which allows one to obtain a consistent collective opinion, from information provided by each expert in terms of multigranular fuzzy estimates. It is based on a linguistic hierarchical model with multigranular sets of linguistic terms, and the choice of the most suitable set is a prerogative of each expert. From the human viewpoint, using such model is advantageous, since it permits each expert to utilize linguistic terms that reflect more adequately the level of uncertainty intrinsic to his evaluation. From the operational viewpoint, the advantage of using such model lies in the fact that it allows one to express the linguistic information in a unique domain, without losses of information, during the discussion process. The proposed consensus scheme supposes that the moderator can interfere in the discussion process in different ways. The intervention can be a request to any expert to update his opinion or can be the adjustment of the weight of each expert`s opinion. An optimal adjustment can be achieved through the execution of an optimization procedure that searches for the weights that maximize a corresponding soft consensus index. In order to demonstrate the usefulness of the presented consensus scheme, a technique for multicriteria analysis, based on fuzzy preference relation modeling, is utilized for solving a hypothetical enterprise strategy planning problem, generated with the use of the Balanced Scorecard methodology. (C) 2009 Elsevier Inc. All rights reserved.