No / In this paper, we illustrate the ways in which Bayesian statistical techniques may be used to enhance chronological resolution when applied to a series of OSL sediment dates. Such application can achieve an optimal chronological model by incorporating stratigraphic and age information. The application to luminescence data is not straightforward owing to the sources of uncertainty in each date, and here we present one solution to overcoming these difficulties, and introduce the concept of "unshared systematic" errors. Using OSL sediment dates from the site of Old Scatness Broch, Shetland Isles, UK, many measured with a high degree of precision, we illustrate some of the ways in which Bayesian techniques may be applied, as a tool for assessing systematic errors when combined with independent chronological information, and to determine the optimum chronological information for specific events and contexts. We provide a detailed procedure for the application of Bayesian methods to OSL dates using the widely available radiocarbon calibration programme OxCal.

Performance regression testing is a difficult task with several intricacies and complexities. In the absence of analysis tools, manual analysis must be conducted which is undoubtedly infeasible. Thereby, in this thesis, an automated performance analysis framework is proposed, aiming to mitigate the faced issues. To make this possible, the adequacy of the data needed to be established. Additionally, a fault detection algorithm had to be developed. From investigating the current state-of-the-art of performance anomaly detection, evidently, statistical models have been utilised far more than classical machine learning, and deep learning. Consequently, based on this knowledge and based on the types of anomalies present in the data, a cumulative sum based statistical method is proposed. The findings demonstrate that the data is adequate for detecting faults, and verifying their validity, as they are consistently observable in several test configurations. However, tests are not performed frequently enough which consequently leads to challenges in identifying the exact locations of faults. The algorithm was evaluated on artificial data with injected faults and could detect over 90 % of anomalies if they were prominent enough. Longer sequences before fault deviations occur, improved the ability of detecting the faults. Thus, further motivating the need to collect data more frequently. On a final note, the automated performance analysis framework successfully improved the efficiency of fault detection, and greater contextual data awareness were achieved through the visualization features. Manual analysis can however detect faults with greater accuracy. On that ground, these results should be interpreted with caution.

Thesis (MComm)--Stellenbosch University, 2011. / ENGLISH ABSTRACT: The analysis of multidimensional (multivariate) data sets is a very important area of research in applied statistics. Over the decades many techniques have been developed to deal with such datasets. The multivariate techniques that have been developed include inferential analysis, regression analysis, discriminant analysis, cluster analysis and many more exploratory methods. Most of these methods deal with cases where the data contain numerical variables. However, there are powerful methods in the literature that also deal with multidimensional binary and count data. The primary purpose of this thesis is to discuss the exploratory and inferential techniques that can be used for binary and count data. In Chapter 2 of this thesis we give the detail of correspondence analysis and canonical correspondence analysis. These methods are used to analyze the data in contingency tables. Chapter 3 is devoted to cluster analysis. In this chapter we explain four well-known clustering methods and we also discuss the distance (dissimilarity) measures available in the literature for binary and count data. Chapter 4 contains an explanation of metric and non-metric multidimensional scaling. These methods can be used to represent binary or count data in a lower dimensional Euclidean space. In Chapter 5 we give a method for inferential analysis called the analysis of distance. This method use a similar reasoning as the analysis of variance, but the inference is based on a pseudo F-statistic with the p-value obtained using permutations of the data. Chapter 6 contains real-world applications of these above methods on two special data sets called the Biolog data and Barents Fish data. The secondary purpose of the thesis is to demonstrate how the above techniques can be performed in the software package R. Several R packages and functions are discussed throughout this thesis. The usage of these functions is also demonstrated with appropriate examples. Attention is also given to the interpretation of the output and graphics. The thesis ends with some general conclusions and ideas for further research. / AFRIKAANSE OPSOMMING: Die analise van meerdimensionele (meerveranderlike) datastelle is ’n belangrike area van navorsing in toegepaste statistiek. Oor die afgelope dekades is daar verskeie tegnieke ontwikkel om sulke data te ontleed. Die meerveranderlike tegnieke wat ontwikkel is sluit in inferensie analise, regressie analise, diskriminant analise, tros analise en vele meer verkennende data analise tegnieke. Die meerderheid van hierdie metodes hanteer gevalle waar die data numeriese veranderlikes bevat. Daar bestaan ook kragtige metodes in die literatuur vir die analise van meerdimensionele binêre en telling data. Die primêre doel van hierdie tesis is om tegnieke vir verkennende en inferensiële analise van binêre en telling data te bespreek. In Hoofstuk 2 van hierdie tesis bespreek ons ooreenkoms analise en kanoniese ooreenkoms analise. Hierdie metodes word gebruik om data in gebeurlikheidstabelle te analiseer. Hoofstuk 3 bevat tegnieke vir tros analise. In hierdie hoofstuk verduidelik ons vier gewilde tros analise metodes. Ons bespreek ook die afstand maatstawwe wat beskikbaar is in die literatuur vir binêre en telling data. Hoofstuk 4 bevat ’n verduideliking van metriese en nie-metriese meerdimensionele skalering. Hierdie metodes kan gebruik word om binêre of telling data in ‘n lae dimensionele Euclidiese ruimte voor te stel. In Hoofstuk 5 beskryf ons ’n inferensie metode wat bekend staan as die analise van afstande. Hierdie metode gebruik ’n soortgelyke redenasie as die analise van variansie. Die inferensie hier is gebaseer op ’n pseudo F-toetsstatistiek en die p-waardes word verkry deur gebruik te maak van permutasies van die data. Hoofstuk 6 bevat toepassings van bogenoemde tegnieke op werklike datastelle wat bekend staan as die Biolog data en die Barents Fish data. Die sekondêre doel van die tesis is om te demonstreer hoe hierdie tegnieke uitgevoer word in the R sagteware. Verskeie R pakette en funksies word deurgaans bespreek in die tesis. Die gebruik van die funksies word gedemonstreer met toepaslike voorbeelde. Aandag word ook gegee aan die interpretasie van die afvoer en die grafieke. Die tesis sluit af met algemene gevolgtrekkings en voorstelle vir verdere navorsing.

Given the increase in popularity of Lifetime Value (LTV), the argument is that the topic will assume an increasingly central role in research and marketing. As such, the decision to assess the state of the field in Lifetime Value Modelling, and outline challenges unique to choice researchers in customer relationship management (CRM). As the research has argued, there are an excess of issues and analytical challenges that remain unresolved. The researcher hopes that this thesis inspires new answers and new approaches to resolve LTV. The scope of this project covers the building of a LTV model through multiple regression. This thesis is exclusively focused on modelling tenure. In this regard, there are a variety of benchmark statistical techniques arising from survival analysis, which could be applied, to tenure modelling. Tenure prediction will be looked at using survival analysis and compared with "crossbreed" data mining techniques that use multiple regression in concurrence with statistical techniques. It will be demonstrated how data mining tools complement the statistical models, and show that their mutual usage overcomes many of the shortcomings of each singular tool set, resulting in LTV models that are both accurate and comprehensible. Bank XYZ is used as an example and is based on a real scenario of one of the Banks of South Africa. / Thesis (M.Sc. (Computer Science))--North-West University, Vaal Triangle Campus, 2009.

Made available in DSpace on 2016-08-10T10:40:22Z (GMT). No. of bitstreams: 1 RAIMUNDA VIEIRA SANTOS DA SILVA.pdf: 968808 bytes, checksum: 4085e6c6bcd3e4d7a87e0bc635163dde (MD5) Previous issue date: 2014-03-19 / The public work execution has great importance for the country´s development, either in economic or socio-political terms. However, according to the information provided by the Brazilian Court of Audit (TCU), there are innumerous irregularities in this king of execution in the country and among them, contract amendments. Contract amendments, whether of value or time, cause losses both for society and for public administration. In this work, we seek to analyze the events that contribute to changes in the construction planning time of the Federal Institutes of Education of Goiás and Tocantins, using statistical models and data mining techniques. The use of quantitative methods in this analysis shows that there are relationships or associations between the characteristics of the works and their amendments. / A execução de obras públicas possui grande importância para o desenvolvimento de um país, seja em termos econômicos ou político-sociais. Entretanto, de acordo constatações realizadas pelo Tribunal de Contas da União (TCU), são inúmeras as irregularidades verificadas na execução das obras públicas no país e dentre elas, os aditivos contratuais. Os aditivos contratuais, sejam de valor ou de tempo, ocasionam prejuízos tanto para a sociedade quanto para a administração pública. Neste trabalho, procura-se analisar as situações que contribuem para as alterações no cronograma das obras públicas dos Institutos Federais de Ensino de Goiás e Tocantins, utilizando-se de modelos estatísticos e de técnicas de mineração de dados. A utilização destes métodos quantitativos na análise da execução das obras públicas mostra que existem relações ou associações entre as características das obras e seus aditivos.

O ser humano vem provocando mudanças no clima, por meio da transformação da natureza, seja para sua ocupação do espaço, sejam para desenvolver suas atividades. Na medida em que o homem se concentra em determinadas áreas, a pressão sobre os condicionantes naturais aumenta. As cidades constituem um dos melhores exemplos da concentração de pessoas e atividades em um mesmo lugar e também da intensa interferência do homem no ambiente. As mudanças ambientais provocadas pelas ações antrópicas geram consequências a ponto de criar um clima especial, o Clima Urbano. Ao detalhar este clima verifica-se que no contexto da cidade ocorrem diversos microclimas diretamente relacionados com a presença dos elementos que compreende o ambiente produzido pelo processo de urbanização - a área urbana. A intensidade com que o Clima Urbano se faz perceber depende do tamanho da cidade, do modelo de ocupação, das atividades desenvolvidas, número de habitantes e do grau de alterações provocadas no meio ambiente. A área urbana de Ponta Grossa, no estado do Paraná, uma cidade subtropical de 310 mil habitantes, possui relevo irregular, com muitos fundos de vale, com extensa ocupação horizontal que se estende para todas as direções e vertical principalmente no centro, constitui a área de estudo do presente trabalho. Na busca de identificar o clima da cidade de Ponta Grossa, foi desenvolvido trabalho de campo para a produção de dados sobre o clima local, os quais foram tratados através de técnicas estatísticas e com programas de geoprocessamento, que resultou em um vasto material cartográfico, que permitiu fazer algumas inferências importantes sobre o Clima Urbano. As conclusões mostram que o Clima Urbano de Ponta Grossa, como em outras áreas urbanas é condicionado pelas construções, pela circulação de veículos, pela ausência ou presença da arborização urbana e pelos condicionantes naturais, como altitude e a exposição de vertentes. Além disso, as condições climáticas regionais também atuam de forma contundente na cidade, como no caso do avanço das frentes frias, quando da entrada de massas de ar e da ação dos ventos que predominantemente sopram de leste, nordeste e sudeste. Por fim concluiu-se também que ocorre a formação da ilha de calor no centro da cidade, porém com deslocamentos para o sul da cidade, até onde se verifica um processo mais intenso de urbanização, assim como para oeste onde a combinação da urbanização, intensa presença de fundos de vale com a exposição de vertentes de forma predominante para o quadrante norte, favorecem as temperaturas mais elevadas. Por fim, os resultados apontam para o fato de que o estudo do clima urbano de Ponta Grossa pode ser utilizado para o planejamento urbano e revisão do plano diretor, pois há indicativos de que é possível melhorar a qualidade de vida da população de algumas áreas da cidade com um planejamento que leve em consideração as características do clima local. / The human being has led to changes in climate through the transformation of nature, whether for its occupation of space, is to develop its activities. To the extent that the man is concentrated in certain áreas, pressure on the natural conditions increases. The city is one of the best examples of the concentration of people and activities in one place and also the intense human interference in the environment. Environmental changes caused by human actions generate consequences as to create a special climate, the urban climate. By describing this climate it appears that in the context of the city different microclimates occur directly related to the presence of the elements comprising the environment produced by the process of urbanization - the urban área. The intensity with which the urban climate makes them perceive depends on the size of the city, the model of occupation, the activities developed, number of inhabitants and the degree of induced changes in the environment. The urban área of Ponta Grossa, Parana state, a subtropical city of 310 thousand inhabitants, has irregular relief, with many of the valleys, with extensive occupation horizontal stretching in all directions and especially in the vertical center, is the área study of this work. In seeking to identify the climate of the city of Ponta Grossa, was developed fieldwork for the production of data on local climate, which were treated by statistical techniques and GIS programs, which resulted in an extensive map material, which allowed to make some important inferences about the urban climate. The findings show that the urban climate of Ponta Grossa, as in other urban áreas is affected by the construction, the movement of vehicles, the absence or presence of urban tree planting and by natural conditions such as altitude and exposure of slopes. Moreover, the regional climate conditions also act forcefully in the city, as in the advance of cold fronts, when the entry of air masses and the action of the winds predominantly blow from the east, northeast and southeast. Finally it was felt that there is the formation of heat islands in the city center, but with shifts to the south of the city, even where there is a more intense process of urbanization, and to the west where the combination of urbanization, intensive presence of the valleys with exposure to áreas of predominantly North quadrant to favor the higher temperatures. Finally, the results point to the fact that the study of urban climate of Ponta Grossa can be used for planning and review of the master plan, as there are indications that it is possible to improve the quality of life of the population in some áreas of city with a plan that takes into account the characteristics of the local climate.

Given the increase in popularity of Lifetime Value (LTV), the argument is that the topic will assume an increasingly central role in research and marketing. As such, the decision to assess the state of the field in Lifetime Value Modelling, and outline challenges unique to choice researchers in customer relationship management (CRM). As the research has argued, there are an excess of issues and analytical challenges that remain unresolved. The researcher hopes that this thesis inspires new answers and new approaches to resolve LTV. The scope of this project covers the building of a LTV model through multiple regression. This thesis is exclusively focused on modelling tenure. In this regard, there are a variety of benchmark statistical techniques arising from survival analysis, which could be applied, to tenure modelling. Tenure prediction will be looked at using survival analysis and compared with "crossbreed" data mining techniques that use multiple regression in concurrence with statistical techniques. It will be demonstrated how data mining tools complement the statistical models, and show that their mutual usage overcomes many of the shortcomings of each singular tool set, resulting in LTV models that are both accurate and comprehensible. Bank XYZ is used as an example and is based on a real scenario of one of the Banks of South Africa. / Thesis (M.Sc. (Computer Science))--North-West University, Vaal Triangle Campus, 2009.

Given the increase in popularity of Lifetime Value (LTV), the argument is that the topic will assume an increasingly central role in research and marketing. As such, the decision to assess the state of the field in Lifetime Value Modelling, and outline challenges unique to choice researchers in customer relationship management (CRM). As the research has argued, there are an excess of issues and analytical challenges that remain unresolved. The researcher hopes that this thesis inspires new answers and new approaches to resolve LTV. The scope of this project covers the building of a LTV model through multiple regression. This thesis is exclusively focused on modelling tenure. In this regard, there are a variety of benchmark statistical techniques arising from survival analysis, which could be applied, to tenure modelling. Tenure prediction will be looked at using survival analysis and compared with "crossbreed" data mining techniques that use multiple regression in concurrence with statistical techniques. It will be demonstrated how data mining tools complement the statistical models, and show that their mutual usage overcomes many of the shortcomings of each singular tool set, resulting in LTV models that are both accurate and comprehensible. Bank XYZ is used as an example and is based on a real scenario of one of the Banks of South Africa. / Thesis (M.Sc. (Computer Science))--North-West University, Vaal Triangle Campus, 2009.

O ser humano vem provocando mudanças no clima, por meio da transformação da natureza, seja para sua ocupação do espaço, sejam para desenvolver suas atividades. Na medida em que o homem se concentra em determinadas áreas, a pressão sobre os condicionantes naturais aumenta. As cidades constituem um dos melhores exemplos da concentração de pessoas e atividades em um mesmo lugar e também da intensa interferência do homem no ambiente. As mudanças ambientais provocadas pelas ações antrópicas geram consequências a ponto de criar um clima especial, o Clima Urbano. Ao detalhar este clima verifica-se que no contexto da cidade ocorrem diversos microclimas diretamente relacionados com a presença dos elementos que compreende o ambiente produzido pelo processo de urbanização - a área urbana. A intensidade com que o Clima Urbano se faz perceber depende do tamanho da cidade, do modelo de ocupação, das atividades desenvolvidas, número de habitantes e do grau de alterações provocadas no meio ambiente. A área urbana de Ponta Grossa, no estado do Paraná, uma cidade subtropical de 310 mil habitantes, possui relevo irregular, com muitos fundos de vale, com extensa ocupação horizontal que se estende para todas as direções e vertical principalmente no centro, constitui a área de estudo do presente trabalho. Na busca de identificar o clima da cidade de Ponta Grossa, foi desenvolvido trabalho de campo para a produção de dados sobre o clima local, os quais foram tratados através de técnicas estatísticas e com programas de geoprocessamento, que resultou em um vasto material cartográfico, que permitiu fazer algumas inferências importantes sobre o Clima Urbano. As conclusões mostram que o Clima Urbano de Ponta Grossa, como em outras áreas urbanas é condicionado pelas construções, pela circulação de veículos, pela ausência ou presença da arborização urbana e pelos condicionantes naturais, como altitude e a exposição de vertentes. Além disso, as condições climáticas regionais também atuam de forma contundente na cidade, como no caso do avanço das frentes frias, quando da entrada de massas de ar e da ação dos ventos que predominantemente sopram de leste, nordeste e sudeste. Por fim concluiu-se também que ocorre a formação da ilha de calor no centro da cidade, porém com deslocamentos para o sul da cidade, até onde se verifica um processo mais intenso de urbanização, assim como para oeste onde a combinação da urbanização, intensa presença de fundos de vale com a exposição de vertentes de forma predominante para o quadrante norte, favorecem as temperaturas mais elevadas. Por fim, os resultados apontam para o fato de que o estudo do clima urbano de Ponta Grossa pode ser utilizado para o planejamento urbano e revisão do plano diretor, pois há indicativos de que é possível melhorar a qualidade de vida da população de algumas áreas da cidade com um planejamento que leve em consideração as características do clima local. / The human being has led to changes in climate through the transformation of nature, whether for its occupation of space, is to develop its activities. To the extent that the man is concentrated in certain áreas, pressure on the natural conditions increases. The city is one of the best examples of the concentration of people and activities in one place and also the intense human interference in the environment. Environmental changes caused by human actions generate consequences as to create a special climate, the urban climate. By describing this climate it appears that in the context of the city different microclimates occur directly related to the presence of the elements comprising the environment produced by the process of urbanization - the urban área. The intensity with which the urban climate makes them perceive depends on the size of the city, the model of occupation, the activities developed, number of inhabitants and the degree of induced changes in the environment. The urban área of Ponta Grossa, Parana state, a subtropical city of 310 thousand inhabitants, has irregular relief, with many of the valleys, with extensive occupation horizontal stretching in all directions and especially in the vertical center, is the área study of this work. In seeking to identify the climate of the city of Ponta Grossa, was developed fieldwork for the production of data on local climate, which were treated by statistical techniques and GIS programs, which resulted in an extensive map material, which allowed to make some important inferences about the urban climate. The findings show that the urban climate of Ponta Grossa, as in other urban áreas is affected by the construction, the movement of vehicles, the absence or presence of urban tree planting and by natural conditions such as altitude and exposure of slopes. Moreover, the regional climate conditions also act forcefully in the city, as in the advance of cold fronts, when the entry of air masses and the action of the winds predominantly blow from the east, northeast and southeast. Finally it was felt that there is the formation of heat islands in the city center, but with shifts to the south of the city, even where there is a more intense process of urbanization, and to the west where the combination of urbanization, intensive presence of the valleys with exposure to áreas of predominantly North quadrant to favor the higher temperatures. Finally, the results point to the fact that the study of urban climate of Ponta Grossa can be used for planning and review of the master plan, as there are indications that it is possible to improve the quality of life of the population in some áreas of city with a plan that takes into account the characteristics of the local climate.

Traditional forecasting models have been widely used for decision-making in production, finance and energy. Such is the case of the ARIMA models, developed in the 1970s by George Box and Gwilym Jenkins [1], which incorporate characteristics of the past models of the same series, according to their autocorrelation. This work compares advanced statistical methods for determining the demand for electricity in Colombia, including the SARIMA, econometric and Bayesian methods.