Neste trabalho estendemos os modelos mistos semiparamétricos propostos por Zhang et al. (1998) para uma classe mais geral de modelos, a qual denominamos modelos mistos aditivos semiparamétricos com erros de contornos elípticos. Com essa nova abordagem, flexibilizamos a curtose da distribuição dos erros possibilitando a escolha de distribuições com caudas mais leves ou mais pesadas do que as caudas da distribuição normal padrão. Funções de verossimilhança penalizadas são aplicadas para a obtenção das estimativas de máxima verossimilhança com os respectivos erros padrão aproximados. Essas estimativas, sob erros de caudas pesadas, são robustas no sentido da distância de Mahalanobis contra observações aberrantes. Curvaturas de influência local são obtidas segundo alguns esquemas de perturbação e gráficos de diagnóstico são propostos. Exemplos ilustrativos são apresentados em que ajustes sob erros normais são comparados, através das metodologias de sensibilidade desenvolvidas no trabalho, com ajustes sob erros de contornos elípticos. / In this work we extend the models proposed by Zhang et al. (1998) to a more general class of models, know as semiparametric additive mixed models with elliptical errors in order to allow distributions with heavier or lighter tails than the normal ones. Penalized likelihood equations are applied to derive the maximum likelihood estimates which appear to be robust against outlying observations in the sense of the Mahalanobis distance. In order to study the sensitivity of the penalized estimates under some usual perturbation schemes in the model or data, the local influence curvatures are derived and some diagnostic graphics are proposed. Motivating examples preliminary analyzed under normal errors are reanalyzed under some appropriate elliptical errors. The local influence approach is used to compare the sensitivity of the model estimates.

A teoria do valor extremo é aplicada em áreas de pesquisa tais como hidrologia, estudos de poluição, engenharia de materiais, controle de tráfego e economia. A distribuição valor extremo ou Gumbel é amplamente utilizada na modelagem de valores extremos de fenômenos da natureza e no contexto de análise de sobrevivência para modelar o logaritmo do tempo de vida. A modelagem de valores extremos de fenômenos da natureza tais como velocidade de vento, nível da água de rio ou mar, altura de onda ou umidade é importante em estatística ambiental pois o conhecimento de valores extremos de tais eventos é crucial na prevenção de catátrofes. Ultimamente esta teoria é de particular interesse pois fenômenos extremos da natureza têm sido mais comuns e intensos. A maioria dos artigos sobre teoria do valor extremo para modelagem de dados considera amostras de tamanho moderado ou grande. A distribuição Gumbel é frequentemente incluída nas análises mas a qualidade do ajuste pode ser pobre em função de presença de ouliers. Investigamos modelagem estatística de eventos extremos com base na teoria de valores extremos. Consideramos um modelo de regressão valor extremo introduzido por Barreto-Souza & Vasconcellos (2011). Os autores trataram da questão de corrigir o viés do estimador de máxima verossimilhança para pequenas amostras. Nosso primeiro objetivo é deduzir ajustes para testes de hipótese nesta classe de modelos. Derivamos a estatística da razão de verossimilhanças ajustada de Skovgaard (2001) e cinco ajustes da estatística da razão de verossimilhanças sinalizada, que foram propostos por Barndorff-Nielsen (1986, 1991), DiCiccio & Martin (1993), Skovgaard (1996), Severini (1999) e Fraser et al. (1999). As estatísticas ajustadas são aproximadamente distribuídas como uma distribuição $\\chi^2$ e normal padrão com alto grau de acurácia. Os termos dos ajustes têm formas compactas simples que podem ser facilmente implementadas em softwares disponíveis. Comparamos a performance do teste da razão de verossimilhanças, do teste da razão de verossimilanças sinalizada e dos testes ajustados obtidos neste trabalho em amostras pequenas. Ilustramos uma aplicação dos testes usuais e suas versões modificadas em conjuntos de dados reais. As distribuições das estatísticas ajustadas são mais próximas das respectivas distribuições limites comparadas com as distribuições das estatísticas usuais quando o tamanho da amostra é relativamente pequeno. Os resultados de simulação indicaram que as estatísticas ajustadas são recomendadas para inferência em modelo de regressão valor extremo quando o tamanho da amostra é moderado ou pequeno. Parcimônia é importante quando os dados são escassos, mas flexibilidade também é crucial pois um ajuste pobre pode levar a uma conclusão completamente errada. Uma revisão da literatura foi feita para listar as distribuições que são generalizações da distribuição Gumbel. Nosso segundo objetivo é avaliar a parcimônia e flexibilidade destas distribuições. Com este propósito, comparamos tais distribuições através de momentos, coeficientes de assimetria e de curtose e índice da cauda. As famílias mais amplas obtidas pela inclusão de parâmetros adicionais, que têm a distribuição Gumbel como caso particular, apresentam assimetria e curtose flexíveis enquanto a distribuição Gumbel apresenta tais características constantes. Dentre estas distribuições, a distribuição valor extremo generalizada é a única com índice da cauda que pode ser qualquer número real positivo enquanto os índices da cauda das outras distribuições são zero. Observamos que algumas generalizações da distribuição Gumbel estudadas na literatura são não identificáveis. Portanto, para estes modelos a interpretação e estimação de parâmetros individuais não é factível. Selecionamos as distribuições identificáveis e as ajustamos a um conjunto de dados simulado e a um conjunto de dados reais de velocidade de vento. Como esperado, tais distribuições se ajustaram bastante bem ao conjunto de dados simulados de uma distribuição Gumbel. A distribuição valor extremo generalizada e a mistura de duas distribuições Gumbel produziram melhores ajustes aos dados do que as outras distribuições na presença não desprezível de observações discrepantes que não podem ser acomodadas pela distribuição Gumbel e, portanto, sugerimos que tais distribuições devem ser utilizadas neste contexto. / The extreme value theory is applied in research fields such as hydrology, pollution studies, materials engineering, traffic management, economics and finance. The Gumbel distribution is widely used in statistical modeling of extreme values of a natural process such as rainfall and wind. Also, the Gumbel distribution is important in the context of survival analysis for modeling lifetime in logarithmic scale. The statistical modeling of extreme values of a natural process such as wind or humidity is important in environmental statistics; for example, understanding extreme wind speed is crucial in catastrophe/disaster protection. Lately this is of particular interest as extreme natural phenomena/episodes are more common and intense. The majority of papers on extreme value theory for modeling extreme data is supported by moderate or large sample sizes. The Gumbel distribution is often considered but the resulting fit may be poor in the presence of ouliers since its skewness and kurtosis are constant. We deal with statistical modeling of extreme events data based on extreme value theory. We consider a general extreme-value regression model family introduced by Barreto-Souza & Vasconcellos (2011). The authors addressed the issue of correcting the bias of the maximum likelihood estimators in small samples. Here, our first goal is to derive hypothesis test adjustments in this class of models. We derive Skovgaard\'s adjusted likelihood ratio statistics Skovgaard (2001) and five adjusted signed likelihood ratio statistics, which have been proposed by Barndorff-Nielsen (1986, 1991), DiCiccio & Martin (1993), Skovgaard (1996), Severini (1999) and Fraser et al. (1999). The adjusted statistics are approximately distributed as $\\chi^2$ and standard normal with high accuracy. The adjustment terms have simple compact forms which may be easily implemented by readily available software. We compare the finite sample performance of the likelihood ratio test, the signed likelihood ratio test and the adjusted tests obtained in this work. We illustrate the application of the usual tests and their modified versions in real datasets. The adjusted statistics are closer to the respective limiting distribution compared to the usual ones when the sample size is relatively small. Simulation results indicate that the adjusted statistics can be recommended for inference in extreme value regression model with small or moderate sample size. Parsimony is important when data are scarce, but flexibility is also crucial since a poor fit may lead to a completely wrong conclusion. A literature review was conducted to list distributions which nest the Gumbel distribution. Our second goal is to evaluate their parsimony and flexibility. For this purpose, we compare such distributions regarding moments, skewness, kurtosis and tail index. The larger families obtained by introducing additional parameters, which have Gumbel embedded in, present flexible skewness and kurtosis while the Gumbel distribution skewness and kurtosis are constant. Among these distributions the generalized extreme value is the only one with tail index that can be any positive real number while the tail indeces of the other distributions investigated here are zero. We notice that some generalizations of the Gumbel distribution studied in the literature are not indetifiable. Hence, for these models meaningful interpretation and estimation of individual parameters are not feasible. We select the identifiable distributions and fit them to a simulated dataset and to real wind speed data. As expected, such distributions fit the Gumbel simulated data quite well. The generalized extreme value distribution and the two-component extreme value distribution fit the data better than the others in the non-negligible presence of outliers that cannot be accommodated by the Gumbel distribution, and therefore we suggest them to be applied in this context.

Made available in DSpace on 2017-07-10T19:24:09Z (GMT). No. of bitstreams: 1 tese__fabiana.pdf: 3413093 bytes, checksum: 69eef866f8ca47e7714ae83768804879 (MD5) Previous issue date: 2016-02-02 / Understanding the spatial distribution knowledge regarding georeferenced data has been essencial to various areas including agriculture. Thus, several trials have been carried out. However, most of these studies assume that the underlying stochastic process is Gaussian. When the data associated with this process do not present normality, data transformations are applied. And though the use of these transformations has presented satisfactory results, it is important to consider models which take into account the characteristics of such phenomenon. It may be more appropriate than using a normal model. So, this trial aimed at proposing a spatial model based on the Birnbaum-Saunders distribution (BS). This distribution has been shown effective to model data that take positive values and whose behavior presents positive asymmetry and unimodality. Thefore, this trial has proposed a methodology that includes the formulation of the spatial Birnbaum-Saunders model , estimation of its parameters using maximum likelihood (ML), and application of diagnostic techniques which can detect the sensitivity of the model to atypical data and evaluate the proposed model through a simulation study and studies using real data sets of agricultural engineering. These data were obtadined in a 167.35-ha commercial area for grain production, in Cascavel city, to validate the studied model. In the study with simulated data and large samples, estimation parameters and diagnostic analysis showed a good performance. According to the study with real data, calculations of AIC (Akaike s information criterion) and BIC (Bayesian information criterion) indexes, Bayes factor as well as Q-Q plots constrution have shown that the proposed model is appropriate to fit the obtained data. Influential cases were detected, and their removal from data set caused a considerable change in contour maps. It is therefore concluided that Birnbaum-Saunders spatial model is adequate to carry out studies with spatially correlated data. Is is also an alternative model to the normal model when the data set present positive asymmetrical distribution / O conhecimento da distribuição espacial de dados georrefenciados é de interesse de diversas áreas do conhecimento, incluindo a área agrícola. Neste sentido, diversos trabalhos já foram realizados; no entanto, a maioria destes trabalhos assumem que o processo estocástico subjacente é gaussiano. Quando os dados associados com este processo não apresentam normalidade, transformações de dados são usadas. E ainda que o uso dessas transformações tenha apresentado resultados satisfatórios, considerar modelos que levem em conta as características do fenômeno pode ser mais adequado do que a utilização do modelo normal. O objetivo deste trabalho é propor um modelo espacial baseado na distribuição Birnbaum-Saunders (BS). Esta distribuição tem se mostrado eficiente para modelar conjuntos de dados formados por valores estritamente positivos e cujo comportamento apresenta assimetria positiva e unimodalidade. A metodologia proposta neste trabalho inclui a formulação do modelo espacial Birnbaum-Saunders, a estimação de seus parâmetros utilizando o método de máxima verossimilhança (ML), a aplicação de técnicas de diagnóstico que permitem detectar a sensibilidade do modelo a dados atípicos, a avaliação do modelo proposto por um estudo de simulação e aplicação da metodologia desenvolvida em análise de dados reais da área agrícola. Os dados utilizados para validação do modelo estudado foram obtidos em uma área comercial de produção de grãos de 167,35 ha de Cascavel. No estudo com dados simulados, para amostras grandes, a estimação dos parâmetros e a análise de diagnóstico apresentaram boa performance. No estudo com dados reais, os cálculos dos índices AIC, BIC e fator Bayes bem como a construção de Q-Q plots mostraram que o modelo proposto é adequado para ajustar os dados. Casos influentes foram detectados e suas retiradas do conjunto de dados causaram uma mudança considerável nos mapas de contorno. Conclui-se portanto, que o modelo espacial Birnbaum-Saunders é adequado para realização de estudos com dados espacialmente correlacionados, e é um modelo alternativo ao modelo normal quando o conjunto de dados apresenta distribuição assimétrica positiva

Made available in DSpace on 2017-05-12T14:47:25Z (GMT). No. of bitstreams: 1 tese__fabiana.pdf: 3413093 bytes, checksum: 69eef866f8ca47e7714ae83768804879 (MD5) Previous issue date: 2016-02-02 / Understanding the spatial distribution knowledge regarding georeferenced data has been essencial to various areas including agriculture. Thus, several trials have been carried out. However, most of these studies assume that the underlying stochastic process is Gaussian. When the data associated with this process do not present normality, data transformations are applied. And though the use of these transformations has presented satisfactory results, it is important to consider models which take into account the characteristics of such phenomenon. It may be more appropriate than using a normal model. So, this trial aimed at proposing a spatial model based on the Birnbaum-Saunders distribution (BS). This distribution has been shown effective to model data that take positive values and whose behavior presents positive asymmetry and unimodality. Thefore, this trial has proposed a methodology that includes the formulation of the spatial Birnbaum-Saunders model , estimation of its parameters using maximum likelihood (ML), and application of diagnostic techniques which can detect the sensitivity of the model to atypical data and evaluate the proposed model through a simulation study and studies using real data sets of agricultural engineering. These data were obtadined in a 167.35-ha commercial area for grain production, in Cascavel city, to validate the studied model. In the study with simulated data and large samples, estimation parameters and diagnostic analysis showed a good performance. According to the study with real data, calculations of AIC (Akaike s information criterion) and BIC (Bayesian information criterion) indexes, Bayes factor as well as Q-Q plots constrution have shown that the proposed model is appropriate to fit the obtained data. Influential cases were detected, and their removal from data set caused a considerable change in contour maps. It is therefore concluided that Birnbaum-Saunders spatial model is adequate to carry out studies with spatially correlated data. Is is also an alternative model to the normal model when the data set present positive asymmetrical distribution / O conhecimento da distribuição espacial de dados georrefenciados é de interesse de diversas áreas do conhecimento, incluindo a área agrícola. Neste sentido, diversos trabalhos já foram realizados; no entanto, a maioria destes trabalhos assumem que o processo estocástico subjacente é gaussiano. Quando os dados associados com este processo não apresentam normalidade, transformações de dados são usadas. E ainda que o uso dessas transformações tenha apresentado resultados satisfatórios, considerar modelos que levem em conta as características do fenômeno pode ser mais adequado do que a utilização do modelo normal. O objetivo deste trabalho é propor um modelo espacial baseado na distribuição Birnbaum-Saunders (BS). Esta distribuição tem se mostrado eficiente para modelar conjuntos de dados formados por valores estritamente positivos e cujo comportamento apresenta assimetria positiva e unimodalidade. A metodologia proposta neste trabalho inclui a formulação do modelo espacial Birnbaum-Saunders, a estimação de seus parâmetros utilizando o método de máxima verossimilhança (ML), a aplicação de técnicas de diagnóstico que permitem detectar a sensibilidade do modelo a dados atípicos, a avaliação do modelo proposto por um estudo de simulação e aplicação da metodologia desenvolvida em análise de dados reais da área agrícola. Os dados utilizados para validação do modelo estudado foram obtidos em uma área comercial de produção de grãos de 167,35 ha de Cascavel. No estudo com dados simulados, para amostras grandes, a estimação dos parâmetros e a análise de diagnóstico apresentaram boa performance. No estudo com dados reais, os cálculos dos índices AIC, BIC e fator Bayes bem como a construção de Q-Q plots mostraram que o modelo proposto é adequado para ajustar os dados. Casos influentes foram detectados e suas retiradas do conjunto de dados causaram uma mudança considerável nos mapas de contorno. Conclui-se portanto, que o modelo espacial Birnbaum-Saunders é adequado para realização de estudos com dados espacialmente correlacionados, e é um modelo alternativo ao modelo normal quando o conjunto de dados apresenta distribuição assimétrica positiva

Savanna woodlands are vitally important in providing ecological services (e.g. erosion protection, micro-climate) and economic services (e.g. timber, food, fodder non-wood products, and wild-life habitats) that sustain local livelihoods and national economies. Increasing demands and the need for sustainable savanna woodland resource management requires that the ecological, economic, social and cultural values of these resources be explored and brought to the attention of decision makers and the general public. The identification and better understanding of the structure and dynamics of woodland community types, patterns of species distribution and quantitative properties of their diversity is important to the conservation and sustainable management of these woodlands. This study seeks to contribute to a better understanding of Nakasongola woodland community types, species diversity patterns and environment correlates, natural regeneration processes (i.e. sprouting and seedling establishment) and identifying livelihood strategies adopted by households, woody species utilised, and the contribution of charcoal production to household livelihoods. Data on vegetation and environmental variables were collected using 75 rectangular 20 x 50 m (0.1 ha) plots. Data on land use and land cover changes, and relevant associated socio-economic parameters were collected through the analysis of multi-temporal satellite imagery and field observations, as well as interviews of local households and key informants. The basic major livelihood activities for the rural households in this savanna dryland are charcoal production, subsistence crop cultivation and livestock grazing. However, it, sometimes, includes various combinations of activities, i.e. charcoal production and subsistence crop cultivation for both food and cash, and livestock keeping for income generation through selling the livestock products such as milk and, sometimes, the whole animal. At least 24 woody species, including fruit trees (Mangifera indica and Artocarpus heterophyllus), are frequently harvested, including 16 species that are considered the most utilized for charcoal production. Charcoal production, being the major source of income to the rural households, contributes on average US$ 259 ± 46 (S.E.) per household annually. There were significant differences in charcoal production (Kruskal-Wallis; H = 31.42, p < 0.0001), producer sale prices per bag of charcoal (H = 35.62, p < 0.0001), and annual incomes from charcoal production (H = 32.44, p < 0.0001) per households across the 8 sub-counties. Most of the youth (≤ 20 years old) derive their livelihoods from charcoal production, a small amount of trade, offering labour services, livestock keeping, fishing, bee keeping and earth brick making. Charcoal production, livestock keeping and hunting are carried out particularly by men, whereas, crop cultivation, and collection of fire wood, medicinal plants and fruits are carried out, mainly, by women. However, men are also engaged in cultivation only during the rainy seasons. There have been significant land cover changes in the area during the period 1984 to 2001, resulting in a 64% decrease in dense woodland cover, and an 80% increase in areas under cultivation/settlements. These changes are attributed to significant spatial expansion in agriculture increased commercialisation of charcoal production, grazing and human population growth. A total of 44,195 (5,893 plants/ha) woody plants representing 99 species in 67 genera and 31 families were recorded. The most species rich families were Mimosaceae (13), Rubiaceae (9), Moraceae (7), Euphorbiaceae (7), Anacardiaceae (6), Combretaceae (5) and Verbenaceae (5). Density of woody species differed significantly (F2, 72 = 6.3, P < 0.003) among land uses, being higher under charcoal production (7,131 ± 755 plants/ha) and cultivation (6,612 ± 665) areas and significantly lower under grazing lands (4,152 ± 525). Community species composition differed significantly (Global RANOSIM = 0.14, p = 0.001) among land use types. All measures of beta-diversity (spatial “turnover” in species composition) showed consistently higher beta-diversity in the grazing land use (βW = 3.1; βT = 3.1), followed by cultivation (βW = 2.8; βT = 3.0) and charcoal production (βW = 2.7; βT = 2.8), suggesting a more heterogeneous spatial distribution of species in the grazing lands. This suggests that variations in the composition and diversity of woody species are to a great extent influenced by land use type and anthropogenic disturbances in this region. Basal area of woody species differed significantly (F2, 72 = 12.0, P < 0.0001) among land uses, being highest under cultivation and charcoal production and significantly lower under grazing. Woody plant density differed (F2,72 = 6.3, P = 0.003) across landuses, being highest under charcoal production and cultivation and significantly lower under grazing. The species that contributed most to both basal area and density across all the land uses were Combretum collinum and Combretum molle. However, different species contributed the next most i.e. Piliostigma thonningii for grazing; Albizia zygia and Harrisonia abyssinica for cultivation and Vepris nobilis for charcoal production areas. For both basal area and abundance of all woody species, the total variance in species-environmental factor relations (for the combined first four canonical axes) was higher than 50%, suggesting a relatively strong influence of the measured environment variables on species composition and distributions. The CCA points to a significant influence of soil Ca2+ and Mg2+ in association with grazing on gradients in the composition and structure of woody species in the savanna woodland of Nakasongola. Resprouting was generally common among the woody species. A total of 2,595 stumps, representing 74 species in 31 families were recorded from all plots. Of these, 98.3% resprouted and were identified to species level. Density of both stumps and total resprout differed significantly (p < 0.05) among the land uses, being higher in charcoal production areas than in grazing and cultivation land uses. For the overall pooled data, resprouts per stump differed significantly among land uses (F2, 456 = 7.75, p = 0.0005), being highest in charcoal production (mean ± S.E.; 14 ± 1) and cultivation (13 ± 1) land uses and lowest under grazing areas (10 ± 1). Generally, the mean number of resprouts per stump increased with increasing stump basal diameter (BD), being highest for BD size class > 41 cm. In relation to stump height, the highest mean resprouts/stump was found on stumps with heights ranging from 0.31- 0.40 m. Based on pooled species data, regression analyses showed weakly significant negative relationships between BD of leading resprouts and number of resprouts/stump (r2 = 0.123, p < 0.0001) and between height of leading resprouts and number of resprouts/stump (r2 = 0.068, p < 0.0001). Density of seedlings of woody species differed significantly among land use types (ANOVA; F2, 72 =5.9, p = 0.004), being highest for cultivation (3,162 ± 440 individuals ha-1), followed by charcoal production (2,416 ± 295 ha-1) and lowest for grazing (1,629 ± 205 ha-1). Composition of seedlings differed significantly among land use types (Global RANOSIM = 0.119, p = 0.001). The distributions and densities of some seedlings were explained by gradients in environmental variables, with edaphic factors (i.e. Ca2+, Mg2+, K+ and organic matter) and charcoal production being the most important. The first two axes of the Canonical Correspondence Analysis (CCA) explained 41.9% of the variance in species – environmental relations and were a reflection of edaphic and charcoal production land use gradients. All of the 16 highly utilized species were well represented in both the juvenile and adult classes, with gradually declining number of individuals with increasing stem size-class. This indicates that most of these species have high regeneration potential. Juvenile:adult tree ratios >1 and negative DSCD slopes indicate good recruitment and probably successful regeneration for these species. The study revealed land cover changes mainly in the dense and medium dense woodlands, reflected by the increase in open woodland, grasslands and cultivation/settlements. These trends threaten the livelihoods of local communities who are entirely dependent on these natural resources. Sustainable management will require the establishment of suitable integrated community-based institutions and management practices, with support from all key stakeholders (i.e. National Forest Authority (NFA)) and local communities. Maintenance of savanna woodland resources and other ecosystem services essential for human well-being will require an effective legal framework to prevent over-exploitation and give incentives for the protection of the fragile savanna woodland vegetation. An appropriate savanna woodland management policy will be required to guide changes in land use that accommodate the requirements of land users, aided by targeted conservation efforts to all woody plants and particularly for the highly utilized species for charcoal production as well as the multipurpose species. In addition, there is urgent need to build local capacity for improved harvesting and utilization of these tree species. This can be achieved through equipping local users with up to date information as well as observing the existing skills.

Dados de tempo de falha são caracterizados pela presença de censuras, que são observações que não foram acompanhadas até a ocorrência de um evento de interesse. Para estudar o comportamento de dados com essa natureza, distribuições de probabilidade são utilizadas. Além disso, é comum se ter uma ou mais variáveis explicativas associadas aos tempos de falha. Dessa forma, o objetivo geral do presente trabalho é propor duas novas distribuições utilizando a função geradora de distribuições gama, no contexto de modelos de regressão em análise de sobrevivência. Essa função possui um parâmetro de forma que permite criar famílias paramétricas de distribuições que sejam flexíveis para capturar uma ampla variedade de comportamentos simétricos e assimétricos. Assim, a distribuição Weibull e a distribuição log-logística foram modificadas, dando origem a duas novas distribuições de probabilidade, denominadas de gama-Weibull e gama-log-logística, respectivamente. Consequentemente, os modelos de regressão locação-escala, de longa-duração e com efeito aleatório foram estudados, considerando as novas distribuições de probabilidade. Para cada um dos modelos propostos, foi utilizado o método da máxima verossimilhança para estimar os parâmetros e algumas medidas de diagnóstico de influência global e local foram calculadas para encontrar possíveis pontos influentes. No entanto, os resíduos foram propostos apenas para os modelos locação-escala para dados com censura à direita e para dados com censura intervalar, bem um estudo de simulação para verificar a distribuição empírica dos resíduos. Outra questão explorada é a introdução dos modelos: gama-Weibull inflacionado de zeros e gama-log-logística inflacionado de zeros, para analisar dados de produção de óleo de copaíba. Por fim, diferentes conjunto de dados foram utilizados para ilustrar a aplicação de cada um dos modelos propostos. / Failure time data are characterized by the presence of censoring, which are observations that were not followed up until the occurrence of an event of interest. To study the behavior of the data of that nature, probability distributions are used. Furthermore, it is common to have one or more explanatory variables associated to failure times. Thus, the goal of this work is given to the generating of gamma distributions function in the context of regression models in survival analysis. This function has a shape parameter that allows create parametric families of distributions that are flexible to capture a wide variety of symmetrical and asymmetrical behaviors. Therefore, through the generating of gamma distributions function, the Weibull distribution and log-logistic distribution were modified to give two new probability distributions: gamma-Weibull and gammalog-logistic. Additionally, location-scale regression models, long-term models and models with random effects were also studied, considering the new distributions. For each of the proposed models, we used the maximum likelihood method to estimate the parameters and some diagnostic measures of global and local influence were calculated for possible influential points. However, residuals have been proposed for data with right censoring and interval-censored data and a simulation study to verify the empirical distribution of the residuals. Another issue explored is the introduction of models: gamma-Weibull inflated zeros and gamma-log-logistic inflated zeros, to analyze production data copaiba oil. Finally, different data set are used to illustrate the application of each of the models.

In 2007, Domínguez-Molina et al. obtained the moment generating function (mgf) of the matrix variate closed skew normal distribution. In this paper, we use their mgf to obtain the first two moments and some additional properties of quadratic forms for the matrix variate skew normal distributions. The quadratic forms are particularly interesting because they are essentially correlation tests that introduce a new type of orthogonality condition.

Neste trabalho propomos a distribuição geométrica de ordem k correlacionada, k &ge; 1, de parâmetros &pi; e &rho; &pi; &isin; (0;1), max{-1, -1-&pi; / &pi; } &le; &rho; &lt; 1, como uma extensão da generalização da distribuição geométrica proposta por Philippou e Muwafi (1980) e utilizando as idéias de Kolev, Minkova e Neytchev (2000) para generalizações de distribuições discretas provenientes de sequências de variáveis binárias. Sendo assim, é também uma releitura da distribuição geométrica de ordem k apresentada por Aki e Hirano (1993). Algumas propriedades da distribuição são demonstradas. Modelos de regressão foram desenvolvidos por ambos os métodos de estimação, clássico e bayesiano. Estudos de dados simulados mostram o comportamento das distribuições e algumas propriedades dos estimadores. A principal motivação em propor este modelo, além de contribuir para generalizações de distribuições discretas, é ter uma alternativa ainda mais adequada para análise de dados reais, pois considera-se o efeito da correlação individual existente pelo parâmetro &rho;. Os ajustes dos modelos foram avaliados e análise de resíduos e de diagnóstico de influência ou divergência também é apresentada. / In this work we propose the correlated geometric distribution of order k, k &ge; 1, with parameters &pi; e &rho; &pi; &isin; (0;1), max{-1, -1-&pi; / &pi; } &le; &rho; &lt; 1, as an extension of the generalized geometric distribution proposed by Philippou e Muwafi (1980) and considering the ideas of Kolev, Minkova e Neytchev (2000) for generalizations of discrete distributions by including an additional parameter &rho;. Thus, it is also a re-reading of the geometric distribution of order k by Aki e Hirano (1993). Some properties of the proposed distribution are presented. Regression models are developed using classical and Bayesian estimation methods. Simulated data studies show the behavior of the distributions and some properties of the estimators. The main motivation in this research, besides contribute to generalizations of discrete distributions, is to propose an alternative analysis and even more suitable for real data, since the effect of the individual correlation is taken into account through the existence of the parameter. The fitted models are evaluated and the residual analysis and diagnosis of influence or divergence are also presented.

In HIV/AIDS studies, viral load (the number of copies of HIV-1 RNA) and CD4 cell counts are important biomarkers of the severity of viral infection, disease progression, and treatment evaluation. Recently, joint models, which have the capability on the bias reduction and estimates' efficiency improvement, have been developed to assess the longitudinal process, survival process, and the relationship between them simultaneously. However, the majority of the joint models are based on mean regression, which concentrates only on the mean effect of outcome variable conditional on certain covariates. In fact, in HIV/AIDS research, the mean effect may not always be of interest. Additionally, if obvious outliers or heavy tails exist, mean regression model may lead to non-robust results. Moreover, due to some data features, like left-censoring caused by the limit of detection (LOD), covariates with measurement errors and skewness, analysis of such complicated longitudinal and survival data still poses many challenges. Ignoring these data features may result in biased inference. Compared to the mean regression model, quantile regression (QR) model belongs to a robust model family, which can give a full scan of covariate effect at different quantiles of the response, and may be more robust to extreme values. Also, QR is more flexible, since the distribution of the outcome does not need to be strictly specified as certain parametric assumptions. These advantages make QR be receiving increasing attention in diverse areas. To the best of our knowledge, few study focuses on the QR-based joint models and applies to longitudinal-survival data with multiple features. Thus, in this dissertation research, we firstly developed three QR-based joint models via Bayesian inferential approach, including: (i) QR-based nonlinear mixed-effects joint models for longitudinal-survival data with multiple features; (ii) QR-based partially linear mixed-effects joint models for longitudinal data with multiple features; (iii) QR-based partially linear mixed-effects joint models for longitudinal-survival data with multiple features. The proposed joint models are applied to analyze the Multicenter AIDS Cohort Study (MACS) data. Simulation studies are also implemented to assess the performance of the proposed methods under different scenarios. Although this is a biostatistical methodology study, some interesting clinical findings are also discovered.

本論文名稱:借鏡英國探討台灣基金市場行銷服務模式之改進方向。主旨係探討國內基金市場行銷現況，旨揭銀行主導銷售的服務模式及費率揭露乃至資金流向疑慮等幾大問題。輔證外國學者學術探討，以及參酌英國共同基金市場發展經驗，提出如統合專業證照、建立類IFA功能、顧問費合法化、開創多元理財商品之開放式交易服務平台及金融監理應扮演角色有關研究心得。 國內商業銀行(前30大)僱用相關理財業務人員已達到4萬餘人，主導共同基金銷售趨勢。但依據國外學者研究，以商業銀行主導基金商品銷售，卻可能衍生問題，形成資金流向扭曲。銀行薪酬制度設計也與理財商品銷售資金流向形成互為因果的連帶關係。銀行能否擺脫佣金高低作為投資建議動力，金融消費者能否得到適合自身的投資組合，仍然存疑。 英國基金市場發展已久，尤其以具有允許收取單一顧問費的獨立財務顧問運用多元化資產組合的包裹基金平台，最具特色。獨立財務顧問運用包裹基金平台給予民眾建議，無論保險、股票、基金、退休金方案等都可透過平台加以交易、組合以及管理等。這樣的投資組合建立、整合交易、保管及管理等模式，提高了消費者和金融業者的管理和投資效率。 參考英國發展基金市場經驗，台灣得以借鏡之處，為加以整合有關金融投資商品證照的分散現狀，並拋開金融機構分業管理的歷史包袱，允許獨立財務顧問存在，給予顧問費收費合法化空間等等。另外，打破現狀，允許商業銀行開放出交易平台供顧問代客戶執行交易，則有助於個別顧問與銀行的良性合作及競爭關係，發展投資理財市場朝向提供金融消費者最適化投資組合的有利環境。 / This paper naming”On the Enhancement of the Mutual Fund Distribution Marketing in Taiwan: Lessons from the UK” subjects local fund marketing status, aims to expose issues of current bank-sales and service model, meanwhile the transparency of sevice rate disclosure. With secondary evidence of foreign scholars’ academic research, concerns of dispute of capital flows as well as other issues i.e.whether consumers get proper sevices and products arised. The status quo in UK fund market is in particular that allows financial advisers to charge a single advisory fee by applying diversified portfolio fund platform and making portforlio suggestion for their clients which includes recommendations and trading of stocks, funds, insurance, pension schemes etc., so as the related services of custody and management. This market will only succeed if it can build a highly efficient operating platform that reduces the operating costs of intermediary firms and product providers alike – creating enhanced value across the value chain that can be shared between customers, intermediaries and product manufacturers (including platforms). Taking into account the development of UK mutual fund market, lessons we have captured such as integration professional licenses, the establishment of classes IFA function, legalization of advisory fees, and create an open trading financial multi-service platform system, etc. Also, financial supervision should play an important role in the research experience.