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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
31

Abordagem clássica e bayesiana para os modelos de séries temporais da família GARMA com aplicações para dados contínuos

Cascone, Marcos Henrique 24 March 2011 (has links)
Made available in DSpace on 2016-06-02T20:06:04Z (GMT). No. of bitstreams: 1 3603.pdf: 602959 bytes, checksum: 3078931e73ff3d01b4122cbac2c7f0a0 (MD5) Previous issue date: 2011-03-24 / Financiadora de Estudos e Projetos / In this work, the aim was to analyze in the classic and bayesian context, the GARMA model with three different continuous distributions: Gaussian, Inverse Gaussian and Gamma. We analyzed the performance and the goodness of fit of the three models, as well as the performance of the coverage percentile. In the classic analyze we consider the maximum likelihood estimator and by simulation study, we verified the consistency, the bias and de mean square error of the models. To the bayesian approach we proposed a non-informative prior distribution for the parameters of the model, resulting in a posterior distribution, which we found the bayesian estimatives for the parameters. This study still was not found in the literature. So, we can observe that the bayesian inference showed a good quality in the analysis of the serie, which can be comprove with the last section of this work. This, consist in the analyze of a real data set corresponding in the rate of tuberculosis cases in metropolitan area of Sao Paulo. The results show that, either the classical and bayesian approach, are good alternatives to describe the behavior of the real time serie. / Neste trabalho, o objetivo foi analisar no contexto clássico e bayesiano, o modelo GARMA com três distribuições contínuas: Gaussiana (Normal), Inversa Gaussiana e Gama, e também o desempenho e a qualidade do ajuste dos modelos de interesse, bem como o desempenho dos percentis de cobertura para eles. Para o estudo clássico foi considerado os estimadores de máxima verossimilhança e por meio de simulação verificou-se a consistência, o viés e o erro quadrático médio dos mesmos. Para a abordagem bayesiana é proposta uma distribuição a priori não informativa para os parâmetros dos modelos resultando em uma distribuição a posteriori, o qual a partir daí pode-se encontrar as estimativas bayesianas para os parâmetros, sendo que este estudo ainda não foi encontrado na literatura. Com isso pode-se observar que a inferência bayesiana mostrou boa eficiência no processo de análise da série, o que pode ser comprovado também com a última etapa do trabalho. Esta, consiste na análise de um conjunto de dados reais correspondente a taxa de casos de tuberculose na região metropolitana de São Paulo. Os resultados mostram que, tanto o estudo clássico quanto o bayesiano, são capazes de descrever bem o comportamento da série.
32

資產模型建構與其資產配置之應用 / Asset Modeling with Non-Gaussian Innovation and Applications to Asset Allocation

陳炫羽, Chen, Hsuan Yu Unknown Date (has links)
因為股票市場常具有厚尾、偏態和峰態的特性且在國際的股票市場之間,股票報酬長存在有尾端相依的情況,所以我們的資產模型不能選用Gaussian分配。 近幾年來,常用GH 分配建構單維度的股票報酬。這篇文章將利用多元仿射JD、多元仿射VG 和多元仿射NIG分配去建構風險性資產的報酬並請應用到資產配置。 建構風險性資產的報酬後,我們提供兩種不同形式的投資組合並且可以導出投資組合的期望值、變異數、偏態和峰態。我們嘗試以投資組合的期望值、變異數、偏態和峰態當成我們的目標函數,然後得出未來最佳的投資組合的權重。為了讓我們的資產配置更加動態和有效率,我們重新估計模型的參數、選擇最佳的投資組合權重,然後重新評估最佳的資產配置在每個決策日期。實證結果發現當股票市場的表現好的時候,我們建議資產配置應使用偏態當成我們的目標函數,但是當股票市場的表現太好的時候,我們建議資產配置應使用變異數當成我們的目標函數。 / Since the stock markets always have the characteristics of heavy-tailness, skewness and kurtosis and there exists tail dependence among the international stock markets, we can’t use the Gaussian distribution as our model. Recently, the generalized hyperbolic (GH) distribution has been suggested to fit the single stock returns. This article will use the multivariate affine JD (MAJD), multivariate affine variance gamma (MAVG) and multivariate affine normal inverse Gaussian (MANIG) distributions to construct the risky asset returns, and apply them to asset allocation. After constructing the risky asset returns, we provide two different forms of portfolio and obtain the mean, variance, skewness, kurtosis of portfolio. We can try to select the optimal weights of portfolio by using the mean, variance, skewness, kurtosis of portfolios as our objective functions. To make our asset allocation more dynamic and efficient, we re-estimate all parameters for our models, select the optimal weights of portfolio, and re-assess the optimal asset allocation at each decision date. Empirically, when the performances of stock markets are good, we suggest that our asset allocation uses the skewness as the objective function. When the performances of stock markets are not good, we suggest that our asset allocation uses the variance as the objective function.
33

Sur les familles des lois de fonction de hasard unimodale : applications en fiabilité et analyse de survie

Saaidia, Noureddine 24 June 2013 (has links)
En fiabilité et en analyse de survie, les distributions qui ont une fonction de hasard unimodale ne sont pas nombreuses, qu'on peut citer: Gaussienne inverse ,log-normale, log-logistique, de Birnbaum-Saunders, de Weibull exponentielle et de Weibullgénéralisée. Dans cette thèse, nous développons les tests modifiés du Chi-deux pour ces distributions tout en comparant la distribution Gaussienne inverse avec les autres. Ensuite nousconstruisons le modèle AFT basé sur la distribution Gaussienne inverse et les systèmes redondants basés sur les distributions de fonction de hasard unimodale. / In reliability and survival analysis, distributions that have a unimodalor $\cap-$shape hazard rate function are not too many, they include: the inverse Gaussian,log-normal, log-logistic, Birnbaum-Saunders, exponential Weibull and power generalized Weibulldistributions. In this thesis, we develop the modified Chi-squared tests for these distributions,and we give a comparative study between the inverse Gaussian distribution and the otherdistributions, then we realize simulations. We also construct the AFT model based on the inverseGaussian distribution and redundant systems based on distributions having a unimodal hazard ratefunction.
34

Highway Development Decision-Making Under Uncertainty: Analysis, Critique and Advancement

El-Khatib, Mayar January 2010 (has links)
While decision-making under uncertainty is a major universal problem, its implications in the field of transportation systems are especially enormous; where the benefits of right decisions are tremendous, the consequences of wrong ones are potentially disastrous. In the realm of highway systems, decisions related to the highway configuration (number of lanes, right of way, etc.) need to incorporate both the traffic demand and land price uncertainties. In the literature, these uncertainties have generally been modeled using the Geometric Brownian Motion (GBM) process, which has been used extensively in modeling many other real life phenomena. But few scholars, including those who used the GBM in highway configuration decisions, have offered any rigorous justification for the use of this model. This thesis attempts to offer a detailed analysis of various aspects of transportation systems in relation to decision-making. It reveals some general insights as well as a new concept that extends the notion of opportunity cost to situations where wrong decisions could be made. Claiming deficiency of the GBM model, it also introduces a new formulation that utilizes a large and flexible parametric family of jump models (i.e., Lévy processes). To validate this claim, data related to traffic demand and land prices were collected and analyzed to reveal that their distributions, heavy-tailed and asymmetric, do not match well with the GBM model. As a remedy, this research used the Merton, Kou, and negative inverse Gaussian Lévy processes as possible alternatives. Though the results show indifference in relation to final decisions among the models, mathematically, they improve the precision of uncertainty models and the decision-making process. This furthers the quest for optimality in highway projects and beyond.
35

Highway Development Decision-Making Under Uncertainty: Analysis, Critique and Advancement

El-Khatib, Mayar January 2010 (has links)
While decision-making under uncertainty is a major universal problem, its implications in the field of transportation systems are especially enormous; where the benefits of right decisions are tremendous, the consequences of wrong ones are potentially disastrous. In the realm of highway systems, decisions related to the highway configuration (number of lanes, right of way, etc.) need to incorporate both the traffic demand and land price uncertainties. In the literature, these uncertainties have generally been modeled using the Geometric Brownian Motion (GBM) process, which has been used extensively in modeling many other real life phenomena. But few scholars, including those who used the GBM in highway configuration decisions, have offered any rigorous justification for the use of this model. This thesis attempts to offer a detailed analysis of various aspects of transportation systems in relation to decision-making. It reveals some general insights as well as a new concept that extends the notion of opportunity cost to situations where wrong decisions could be made. Claiming deficiency of the GBM model, it also introduces a new formulation that utilizes a large and flexible parametric family of jump models (i.e., Lévy processes). To validate this claim, data related to traffic demand and land prices were collected and analyzed to reveal that their distributions, heavy-tailed and asymmetric, do not match well with the GBM model. As a remedy, this research used the Merton, Kou, and negative inverse Gaussian Lévy processes as possible alternatives. Though the results show indifference in relation to final decisions among the models, mathematically, they improve the precision of uncertainty models and the decision-making process. This furthers the quest for optimality in highway projects and beyond.

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