Thesis (Ph. D.)--University of Missouri-Columbia, 1997. / Typescript. Vita. Includes bibliographical references (leaves 96-98). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 1997. / Typescript. Vita. Includes bibliographical references (leaves 96-98). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 2004. / Typescript. Vita. Includes bibliographical references (leaves 46-54). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 2004. / Typescript. Vita. Includes bibliographical references (leaves 46-54). Also available on the Internet.

Thesis (M.A.)--The University of North Carolina at Greensboro, 2008. / Title from PDF t.p. (viewed Aug. 17, 2009). Directed by Kirsten Doehler; submitted to the Dept. of Mathematical Sciences. Includes bibliographical references (p. 56-57).

Source: Dissertation Abstracts International, Volume: 54-08, Section: B, page: 3941. Supervisor: Robert J. Hardy. Includes bibliographical references (leaves 109-114).

Thesis (M.A.S.)--Memorial University of Newfoundland, 2003. / Bibliography: leaves 48-50. Also available online.

Orientador: Josmar Mazucheli / Resumo: Na análise de séries climatológicas, a metodologia conhecida como “análise de frequências” inicia-se, após a verificação da validade de algumas suposições, pela escolha e ajuste de uma distribuição de probabilidade. A etapa mais importante desta análise é a escolha ou seleção da distribuição de probabilidade que melhor descreva o verdadeiro comportamento da variável em estudo. Uma vez adotada uma distribuição de probabilidade que esteja bem ajustada, segundo um ou vários critérios, é de interesse, por exemplo, estimar a probabilidade de que eventos de certa magnitude sejam igualados ou excedidos em T anos. O inverso desta probabilidade é chamado de período de retorno, sendo esta uma medida de extrema importância na avaliação de riscos associados a fenômenos climatológicos. Em princípio, qualquer distribuição de probabilidade com suporte nos números reais positivos pode ser utilizada na descrição do comportamento de séries fluviométricas, pluviométricas, eólicas, entre outras. Em se tratando de séries pluviométricas, formadas, por exemplo, pelas pluviosidades diárias, decendiais, mensais, trimestrais e anuais, as distribuições Gama e Weibull são as mais utilizadas. Nos últimos anos, a partir de métodos específicos, uma infinidade de novas distribuições vêm sendo propostas para a análise de observações contínuas e estritamente positivas, cujas aplicações, em sua grande maioria, restringem-se a dados de sobrevivência e confiabilidade. Nesta dissertação de Mestrado, foram avaliad... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: In the climatological series analysis, a methodology known as “frequency analysis” begins, after the validity of some assumptions, by choice and adjustment of a probability distribution. The most important step of this analysis is the choice or selection of probability distribution that best describes the true behavior of the variable under study. Once a probability distribution, that is well adjusted according to one or several criteria, is adopted, it is of interest, for example, to estimate a probability of events of a certain magnitude that are matched or exceeded in T years. The opposite of this probability is called a return period, which is a measure of extreme importance in the evaluation of risks associated with climatological phenomena. In principle, any probability distribution supported by positive real numbers can be used to describe the behavior of fluviometric, pluviometric and wind series, among others. When it comes to the case of rainfall series, formed, for example, by daily, decendial, monthly, quarterly and annual rainfall, the Gamma and Weibull Distributions are more used. In recent years, from specific methods, a plethora of new distributions are being proposed for an analysis of continuous and strictly positive observations, which applications, for the most part, are restricted to survival and reliability data. In this Master’s dissertation, the performances of the Odd Weibull, Marshall-Olkin Weibull, Exponentiated Weibull and Transmutated Weibull Dist... (Complete abstract click electronic access below) / Mestre

The concept of resilience is increasingly applied to policy-making. However, despite its widespread use, resilience remains poorly defined, open to multiple interpretations, and challenging to translate into practical policy instruments. Three particularly problematic aspects of resilience concern its rigid conceptualisation of adaptation and learning, its de-politicised interpretation of participatory decision-making, and the ill-defined role and relevance of social vulnerability indicators. My research analyses these three aspects within the context of flood risk management in the UK, which is uniquely suited to studying the practicability of a cross-disciplinary concept like resilience, because it connects issues of natural resource management, social planning, and disaster management. First, I analyse two case studies of experimental pilot projects in natural flood management. Through studying project reports, and interviewing stakeholders involved in project implementation, I determine whether the theorised learning-by-doing method in resilience is reflected in experiences from real experimental projects. Secondly, I use one of these case studies to map out the political structure of local participatory bodies in flood management, and also conduct a small survey of local community groups. The purpose of this second study is to determine if collaborative methods can indeed lead to a knowledge-driven policy process as envisioned in resilience literature. Lastly, I use statistical analysis to compare a traditional flood management model and a socio-economic model. The aim of the statistical modelling is to determine whether socio-economic factors are indeed useful for informing flooding policy, and whether they offer new insights not already being used in modern flood management. I find that resilience gives insufficient consideration to the importance of political constraints and economic trade-offs in policy-making, and that evidence for the usefulness of socio-economic factors is inconclusive. Future work could focus on further refining the statistical modelling to pinpoint empirically verifiable indicators of resilience.

A quantidade de novos casos de câncer, o número de mortes causadas por ele e a quantidade de pessoas convivendo com a doença (cinco anos após o diagnóstico) têm crescido em todo o mundo. Em função disso, analisar dados de pacientes com câncer torna-se uma ferramenta necessária para avaliar os programas de tratamento e monitorar o progresso das iniciativas de controle da doença. No que tange a análise, a mortalidade é um dos parâmetros utilizados para avaliar os resultados dessa área e as metodologias tradicionalmente utilizadas compreendem o método de Kaplan-Meier e o modelo de Cox. Ambos, porém, desprezam que um paciente com câncer pode vir a óbito por um câncer diferente do primeiro diagnosticado ou, até mesmo, por causas não relacionadas à doença. Portanto, propomos a utilização e entendimento de métodos de análise de sobrevivência que consideram eventos competitivos a fim avaliar incidências, letalidades e fatores associados ao óbito de pacientes com câncer primário atendidos no Hospital de Clínicas de Porto Alegre entre 2002 e 2009. Os resultados obtidos permitiram um melhor conhecimento dos tipos de cânceres com maiores incidências (pele (1.920 casos), próstata (1.080 casos), brônquios e pulmões (950 casos), mama (893 casos), sistema hematopoiético e reticuloendotelial (654 casos), cólon (573 casos), esôfago (497 casos), estômago (422 casos), neoplasia maligna secundária e não especificada dos gânglios linfáticos (360 casos) e colo do útero (328 casos)) e letalidades (pâncreas (145 óbitos; 57,1%), brônquios e pulmões (527 óbitos; 55,5%) e esôfago (262 óbitos, 52,7%)), considerando os eventos competitivos. Em função das vantagens do método, recomenda-se aos pesquisadores que não desprezem, em seus estudos, situações com eventos competitivos, uma vez que há softwares e diversos materiais disponíveis que auxiliam e facilitam sua aplicação. / The amount of new cancer cases, the number of deaths caused by it, and the number of people living with the disease (five years after the diagnosis) have grown around the world. Due that, analyzing cancer patient’s data becomes a necessary tool for evaluating treatment programs and monitor the progress of the disease control initiatives. Regarding the analysis, mortality is one of the parameters used to evaluate the results of this area and the methodologies traditionally used include the Kaplan-Meier and Cox model. However, these methodologies do not consider the fact that the death of a cancer patient can be caused by a different cancer diagnosed or even by causes unrelated to the disease. Therefore, we propose the use and understanding of survival analysis methods that consider competing events in order to assess incidence, lethality and factors associated with death in patients with primary cancer attended at Hospital de Clínicas de Porto Alegre from 2002 to 2009. The results allowed a better understanding of the types of cancers with higher incidence (skin (1,920 cases), prostate (1,080 cases), bronchi and lungs (950 cases), breast (893 cases), hematopoietic and reticuloendothelial system (654 cases), colon (573 cases), esophagus (497 cases), stomach (422 cases), second malignancy and not specified lymph nodes (360 cases) and cervix (328 cases)) and lethality (pancreas (145 deaths; 57.1%), bronchi and lungs (527 deaths; 55.1%) and esophagus (262 deaths; 52.7%)), considering the competing events. In addition, we also evaluated how gender and age contribute to the risk of death from some cancers: women has bigger risk of death for esophageal cancer, while age was associated with the risk of death for prostate cancer. This study allowed characterizing the profile of cancers attended by the hospital by considering the competing events into the estimates methods. Due the advantages of the method, we recommend to researchers do not despise, in their studies, situations with competing events, since there are many softwares and materials available to help and facilitate its implementation.