978 resultados para Modelos Estatísticos


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A evasão estudantil afeta as universidades, privadas e públicas, no Brasil, trazendo-lhes prejuízos financeiros proporcionais à incidência, respectivamente, de 12% e de 26% no âmbito nacional e de 23% na Universidade de São Paulo (USP), razão pela qual se deve compreender as variáveis que governam o comportamento. Neste contexto, a pesquisa apresenta os prejuízos causados pela evasão e a importância de pesquisá-la na Escola Politécnica da USP (EPUSP): seção 1, desenvolve revisão bibliográfica sobre as causas da evasão (seção 2) e propõe métodos para obter as taxas de evasão a partir dos bancos de dados do Governo Federal e da USP (seção 3). Os resultados estão na seção 4. Para inferir sobre as causas da evasão na EPUSP, analisaram-se bancos de dados que, descritos e tratados na seção 5.1, contêm informações (P. Ex.: tipo de ingresso e egresso, tempo de permanência e histórico escolar) de 16.664 alunos ingressantes entre 1.970 e 2.000, bem como se propuseram modelos estatísticos e se detalharam os conceitos dos testes de hipóteses 2 e t-student (seção 5.2) utilizados na pesquisa. As estatísticas descritivas mostram que a EPUSP sofre 15% de evasão (com maior incidência no 2º ano: 24,65%), que os evadidos permanecem matriculados por 3,8 anos, que a probabilidade de evadir cresce após 6º ano e que as álgebras e os cálculos são disciplinas reprovadoras no 1º ano (seção 5.3). As estatísticas inferenciais demonstraram relação entre a evasão - modo de ingresso na EPUSP e evasão - reprovação nas disciplinas do 1º ano da EPUSP, resultados que, combinados com as estatísticas descritivas, permitiram apontar o déficit vocacional, a falta de persistência, a falta de ambientação à EPUSP e as deficiências na formação predecessora como variáveis responsáveis pela evasão (seção 5.4).

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Tese de mestrado em Matemática Aplicada à Economia e Gestão, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2016

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The soursop (A. muricata) is a fruit rich in minerals especially the potassium content. The commercialization of soursop in natura and processed has increased greatly in recent years. Drying fruit pulp in order to obtain the powdered pulp has been studied, seeking alternatives to ensure the quality of dehydrated products at a low cost of production. The high concentration of sugars reducing present in fruits causes problems of agglomeration and retention during fruit pulp drying in spouted bed dryers. On the other hand in relation to drying of milk and fruit pulp with added milk in spouted bed, promising results are reported in the literature. Based on these results was studied in this work drying of the pulp soursop with added milk in spouted bed with inert particles. The tests were based on a 24 factorial design were evaluated for the effects of milk concentration (30 to 50% m/m), drying air temperature (70 to 90 °C), intermittency time (10 to 14 min), and ratio of air velocity in relation to the minimum spout (1.2 to 1.5) on the rate of production, of powder moisture, yield, rate of drying and thermal efficiency of the process. There were physical and chemical analysis of mixtures, of powders and of mixtures reconstituted by rehydration powders. Were adjusted statistical models of first order to data the rate of production, yield and thermal efficiency, that were statistically significant and predictive. An efficiency greater than 40% under the conditions of 50% milk mixture, at 70 ° C the drying air temperature and 1.5 for the ratio between the air velocity and the minimum spout has been reached. The intermittency time showed no significant effect on the analyzed variables. The final product had moisture in the range of 4.18% to 9.99% and water activity between 0.274 to 0.375. The mixtures reconstituted by rehydration powders maintained the same characteristics of natural blends.

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T he socio - economy of the coastal municipalities of Rio Grande do Norte semiarid coast was analyzed th r ou g h by the actors, ant hropogenic implications, fishing environment and composition of its fish fauna, as well as the trend of product ion landed by the artisanal fleet with the aim of identifying the sustainability and management. In this study, were used participatory methodologies, monthly data of rainfall between September 2001 and December 2010; landings of the artisanal fleet during January 2001 to December 2010; and socioeconomic (IBGE, 2002/2010), (IDEMA, 2011/2012), (MPA, 2010; 2012), UNDP and MS (2013). Based on these data, we performed analysis of variance were performed using the method of Analytic Hierarchy Process (HAP) and s tatistical models of multiple regression and time series. It was identified that the occupation of the coastal and marine zone through salt industry, tourism, shrimp farming, oil and gas and wind energy reconfigured the environment and attracted new actors . Rainfall influenced the catches, of which 35% occur in the rainy season, 40% in the dry season and 25% independent. Production increased 55%, in the period analyzed , being landed in 31 ports spread over 11 municipalities, cap tured in environments mangrov e/ estuarine (23%), coastal (46%) and oceanic (31%). Despite market up 41 species, were commercialized in the region production concentrated in eight, mainly landed in Macau and Caiçara North, by vessels of small and medium - sized (motorized and sailboats) . Highlights included three species ( Hirundichthys affins , Coryphaena hippurus and Opisthonema oglinum ), which together accounted for 63.3% of the whole volume. It was found that the motorized vessels tripled in number while sailboats reduced by half. Landin gs by different types of vessels tend to increase over time, while the small sailboats vessels, decrease. The introduction of more new motorized vessels and sailboats also tend to increase production. The study concluded that GDP and HDI of coastal countie s increased however inequality persisted. The potential of artisanal fishing is in the stage “ unfavorable ” of development and the trend in fish production is to grow over time and with the entry of more vessels. However, it is urgent that the state actions to promote and enhance planning to restore fish stocks in a sustainable and profitable fisheries standards. Therefore, it is recommend the strategic use of natural resources in a sustainable development perspective.

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NASCIMENTO, H. G. ; FERNANDES, L. C. ; SOUSA, M. B. C. . Avaliação da fidedignidade dos ensaios de esteróides fecais realizados no Laboratório de Medidas Hormonais do Departamento de Fisiologia da UFRN. Publica , v. 2, p. 39-48, 2006.

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Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model

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NASCIMENTO, H. G. ; FERNANDES, L. C. ; SOUSA, M. B. C. . Avaliação da fidedignidade dos ensaios de esteróides fecais realizados no Laboratório de Medidas Hormonais do Departamento de Fisiologia da UFRN. Publica , v. 2, p. 39-48, 2006.

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Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model

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Neste trabalho apresentamos a teoria da análise de correlação canónica, uma técnica de análise estatística multivariada para o estudo da relação, simultânea, entre dois, três ou mais grupos de variáveis. Descrevemos a natureza da correlação canónica com três ou mais variáveis, com modelos matemáticos, fazendo uma síntese dos métodos de generalização de correlação canónica nomeadamente o método Ssqcor, método Sumcor, método Ecart, método Maxvar, método Minvar, e o método de Carroll. Apresentamos uma aplicação utilizando dados provenientes do cálculo do Índice de Preços no Consumidor IPC, produzido pelo INE - STP (Instituto Nacional de Estatística de São Tomé e Príncipe), referente ao período 2010 a 2014. Estamos interessados em conhecer as correlações canónicas entre grupos de variáveis relacionadas com o cabaz de produtos pré-estabelecido para o cálculo do índice de preços no consumidor, concretamente os produtos alimentares (PA), produtos para bebidas (PB) e produtos não alimentares (PNA), constituindo assim os três grandes grupos de variáveis da nossa pesquisa.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

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Introdução: A perda transitória da consciência e tónus postural seguido de rápida recuperação é definida como síncope. Tem sido dada atenção a uma síncope de origem central com descida da pressão sistémica conhecida por síncope vasovagal (SVV). Objetivos: A análise da variabilidade da frequência cardíaca (HRV) é uma das principais estratégias para estudar a SVV através de protocolos padrão (por exemplo tilt test). O principal objetivo deste trabalho é compreender a importância relativa de diversas variáveis, tais como pressão arterial diastólica e sistólica, (dBP) e (sBP), volume sistólico (SV) e resistência periférica total (TPR) na HRV. Métodos: Foram usados modelos estatísticos mistos para modelar o comportamento das variáveis acima descritas na HRV. Analisaram-se mais de mil e quinhentas observações de quatro pacientes com SVV, previamente testados com análise espectral clássica para a fase basal (LF/HF=3.01) e fases de tilt (LF/HF=0.64), indicando uma predominância vagal no período tilt. Resultados: O modelo 1 revelou o papel importante da dBP e uma baixa influência de SV, na fase de tilt, relativos à HRV. No modelo 2 a TPR revelou uma baixa influência na HRV na fase de tilt entre os pacientes. Conclusões: Verificou-se que a HRV é influenciada por um conjunto de variáveis fisiológicas, cuja contribuição individual pode ser usada para compreender as flutuações cardíacas. O uso de modelos estatísticos salientou a importância de estudar o papel da dBP e SV na SVV.

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Pós-graduação em Agronomia (Produção Vegetal) - FCAV

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The objective of this study was to determine the seasonal and interannual variability and calculate the trends of wind speed in NEB and then validate the mesoscale numerical model for after engage with the microscale numerical model in order to get the wind resource at some locations in the NEB. For this we use two data sets of wind speed (weather stations and anemometric towers) and two dynamic models; one of mesoscale and another of microscale. We use statistical tools to evaluate and validate the data obtained. The simulations of the dynamic mesoscale model were made using data assimilation methods (Newtonian Relaxation and Kalman filter). The main results show: (i) Five homogeneous groups of wind speed in the NEB with higher values in winter and spring and with lower in summer and fall; (ii) The interannual variability of the wind speed in some groups stood out with higher values; (iii) The large-scale circulation modified by the El Niño and La Niña intensified wind speed for the groups with higher values; (iv) The trend analysis showed more significant negative values for G3, G4 and G5 in all seasons and in the annual average; (v) The performance of dynamic mesoscale model showed smaller errors in the locations Paracuru and São João and major errors were observed in Triunfo; (vi) Application of the Kalman filter significantly reduce the systematic errors shown in the simulations of the dynamic mesoscale model; (vii) The wind resource indicate that Paracuru and Triunfo are favorable areas for the generation of energy, and the coupling technique after validation showed better results for Paracuru. We conclude that the objective was achieved, making it possible to identify trends in homogeneous groups of wind behavior, and to evaluate the quality of both simulations with the dynamic model of mesoscale and microscale to answer questions as necessary before planning research projects in Wind-Energy area in the NEB

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Tese dout., Métodos Quantitativos Aplicados à Economia e à Gestão, Universidade do Algarve, 2009

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Tese de doutoramento, Estatística e Investigação Operacional (Probabilidades e Estatística), Universidade de Lisboa, Faculdade de Ciências, 2014