Finite mixture modeling is a useful statistical technique for clustering individuals based on patterns of responses. The fundamental idea of the mixture modeling approach is to assume there are latent clusters of individuals in the population which each generate their own distinct distribution of observations (multivariate or univariate) which are then mixed up together in the full population. Hence, the name mixture comes from the fact that what we observe is a mixture of distributions. The goal of this model-based clustering technique is to identify what the mixture of distributions is so that, given a particular response pattern, individuals can be clustered accordingly. Commonly, finite mixture models, as well as the special case of latent class analysis, are used on data that inherently involve repeated measures. The purpose of this dissertation is to extend the finite mixture model to allow for the number of repeated measures to be incorporated and contribute to the clustering of individuals rather than measures. The dimension of the repeated measures or simply the count of responses is assumed to follow a truncated Poisson distribution and this information can be incorporated into what we call a dimension informative finite mixture model (DIMM). The outline of this dissertation is as follows. Paper 1 is entitled, "Dimension Informative Mixture Modeling (DIMM) for questionnaire data with an informative number of repeated measures." This paper describes the type of data structures considered and introduces the dimension informative mixture model (DIMM). A simulation study is performed to examine how well the DIMM fits the known specified truth. In the first scenario, we specify a mixture of three univariate normal distributions with different means and similar variances with different and similar counts of repeated measurements. We found that the DIMM predicts the true underlying class membership better than the traditional finite mixture model using a predicted value metric score. In the second scenario, we specify a mixture of two univariate normal distributions with the same means and variances with different and similar counts of repeated measurements. We found that that the count-informative finite mixture model predicts the truth much better than the non-informative finite mixture model. Paper 2 is entitled, "Patterns of Physical Activity in the Northern Manhattan Study (NOMAS) Using Multivariate Finite Mixture Modeling (MFMM)." This is a study that applies a multivariate finite mixture modeling approach to examining and elucidating underlying latent clusters of different physical activity profiles based on four dimensions: total frequency of activities, average duration per activity, total energy expenditure and the total count of the number of different activities conducted. We found a five cluster solution to describe the complex patterns of physical activity levels, as measured by fifteen different physical activity items, among a US based elderly cohort. Adding in a class of individuals who were not doing any physical activity, the labels of these six clusters are: no exercise, very inactive, somewhat inactive, slightly under guidelines, meet guidelines and above guidelines. This methodology improves upon previous work which utilized only the total metabolic equivalent (a proxy of energy expenditure) to classify individuals into inactive, active and highly active. Paper 3 is entitled, "Complex Drug Use Patterns and Associated HIV Transmission Risk Behaviors in an Internet Sample of US Men Who Have Sex With Men." This is a study that applies the count-informative information into a latent class analysis on nineteen binary drug items of drugs consumed within the past year before a sexual encounter. In addition to the individual drugs used, the mixture model incorporated a count of the total number of drugs used. We found a six class solution: low drug use, some recreational drug use, nitrite inhalants (poppers) with prescription erectile dysfunction (ED) drug use, poppers with prescription/non-prescription ED drug use and high polydrug use. Compared to participants in the low drug use class, participants in the highest drug use class were 5.5 times more likely to report unprotected anal intercourse (UAI) in their last sexual encounter and approximately 4 times more likely to report a new sexually transmitted infection (STI) in the past year. Younger men were also less likely to report UAI than older men but more likely to report an STI.

Thesis (Ph.D.) -- Mississippi State University. Department of Industrial and Systems Engineering. / Title from title screen. Includes bibliographical references.

<p>The world of systems engineering methods is changing as rigorous ‘off-the-shelf’ systems engineering methods become more popular. One example of such a systems engineering method is Rational Unified Process. In order to cover all phases in a software development process, and a wide range of project-types, such methods need to be of an impressive size. Thus, the need for configuring such methods in a structured way is increasing accordingly. In this thesis, method configuration is considered as a particular kind of method engineering that focuses on tailoring a standard systems engineering method. We propose a meta-method for method configuration based on two fundamental values: standard systems engineering method’s rationality and reuse. A conceptual framework is designed, introducing the concepts Configuration Package and Configuration Template. A Configuration Package is a pre-made ideal method configuration suitable for a delimited characteristic of a (type of) software artifact, or a (type of) software development project, or a combination thereof. Configuration Templates with different characteristics are built combining a selection of Configuration Packages and used as a base for a situational method. The aim of the proposed meta-method is to ease the burden of configuring the standard systems engineering method in order to reach an appropriate situational method.</p>

No description available.

Access to abstract permanently restricted to Ball State community only. / Background : a survey for rate adaptation -- ABEP metric and channell assessment -- ABEP-based adaptive rate control -- Performance evaluation. / Access to thesis permanently restricted to Ball State community only. / Department of Computer Science

Thesis (Ph.D.)--University of Delaware, 2005. / Principal faculty adviser: Xiang-Gen Xia, Dept. of Electrical & Computer Engineering. Includes bibliographical references.

The practice of developing information systems with the support of information systems development methods is not new. A vast number of systems development methods have been suggested over the years in an attempt to solve the problems a development organisation might encounter. From early approaches like the Waterfall model to more modern monolithic methods such as the Rational Unified Process and the newest approaches exemplified in the Agile methods, the ambition has often been to find the silver bullet and the most effective ways to produce quality systems. Methods are prescriptive by nature as they suggest action and as such they represent rationale. Thus, one can speak of a method rationale as the dimension within methods that motivate their existence. Method rationale is understood as the goal and value rational relations between a method’s underlying philosophy and its proposed actions. During the methods’ evolution, the practice of systems development and the supporting systems development methods have been subjected to research from many perspectives. One possible way to understand the nature of the existing research is to separate it into two fields. The suggested fields have different strengths and weaknesses. The field of traditional research on information systems development (ISD) emphasise relevance in their studies but often overlook aspects of generalisation. The field of method engineering (ME) is highly formalistic and emphasise rigour but often miss aspects concerning relevance, such as the role methods play in peoples daily systems development efforts. In this dissertation, a polarisation of existing systems development method research is suggested in order to find a synthesis more capable of serving as a common ground for method research and for the understanding of the systems development method phenomenon. This is achieved through a proposed extension of the field of ME into the field of extended method engineering (EME). The foundation of the EME is found in the concept of method rationale and a method component concept design capable of carrying and expressing method rationale. The method component concept design is applied, evaluated, and re-designed in three different empirical settings in order to ascertain its practical potential and the benefits in explicating the dimension of method rationale.

The dissertation will outline an object-oriented model from which a next-generation GIS can be derived. The requirements for a spatial information analysis and modeling system can be broken into three primary functional classes: data management (data classification and access), analysis (modeling, optimization, and simulation) and visualization (display of data). These three functional classes can be considered as the primary colors of the spectrum from which the different shades of spatial analysis are composed. Object classes will be developed which will be designed to manipulate the three primary functions as required by the user and the data.

The world of systems engineering methods is changing as rigorous ‘off-the-shelf’ systems engineering methods become more popular. One example of such a systems engineering method is Rational Unified Process. In order to cover all phases in a software development process, and a wide range of project-types, such methods need to be of an impressive size. Thus, the need for configuring such methods in a structured way is increasing accordingly. In this thesis, method configuration is considered as a particular kind of method engineering that focuses on tailoring a standard systems engineering method. We propose a meta-method for method configuration based on two fundamental values: standard systems engineering method’s rationality and reuse. A conceptual framework is designed, introducing the concepts Configuration Package and Configuration Template. A Configuration Package is a pre-made ideal method configuration suitable for a delimited characteristic of a (type of) software artifact, or a (type of) software development project, or a combination thereof. Configuration Templates with different characteristics are built combining a selection of Configuration Packages and used as a base for a situational method. The aim of the proposed meta-method is to ease the burden of configuring the standard systems engineering method in order to reach an appropriate situational method.

Mercado Preditivo (MP) é uma ferramenta que utiliza o mecanismo de preço de mercado para agregar informações dispersas em um grande grupo de pessoas, visando à geração de previsões sobre assuntos de interesse. Trata-se de um método de baixo custo, capaz de gerar previsões de forma contínua e que não exige amostras probabilísticas. Há diversas aplicações para esses mercados, sendo que uma das principais é o prognóstico de resultados eleitorais. Este estudo analisou evidências empíricas da eficácia de um Mercado Preditivo no Brasil, criado para fazer previsões sobre os resultados das eleições gerais do ano de 2014, sobre indicadores econômicos e sobre os resultados de jogos do Campeonato Brasileiro de futebol. A pesquisa teve dois grandes objetivos: i) desenvolver e avaliar o desempenho de um MP no contexto brasileiro, comparando suas previsões em relação a métodos alternativos; ii) explicar o que motiva as pessoas a participarem do MP, especialmente quando há pouca ou nenhuma interação entre os participantes e quando as transações são realizadas com uma moeda virtual. O estudo foi viabilizado por meio da criação da Bolsa de Previsões (BPrev), um MP online que funcionou por 61 dias, entre setembro e novembro de 2014, e que esteve aberto à participação de qualquer usuário da Internet no Brasil. Os 147 participantes registrados na BPrev efetuaram um total de 1.612 transações, sendo 760 no tema eleições, 270 em economia e 582 em futebol. Também foram utilizados dois questionários online para coletar dados demográficos e percepções dos usuários. O primeiro foi aplicado aos potenciais participantes antes do lançamento da BPrev (302 respostas válidas) e o segundo foi aplicado apenas aos usuários registrados, após dois meses de experiência de uso da ferramenta (71 respostas válidas). Com relação ao primeiro objetivo, os resultados sugerem que Mercados Preditivos são viáveis no contexto brasileiro. No tema eleições, o erro absoluto médio das previsões do MP na véspera do pleito foi de 3,33 pontos percentuais, enquanto o das pesquisas de opinião foi de 3,31. Considerando todo o período em que o MP esteve em operação, o desempenho dos dois métodos também foi parecido (erro absoluto médio de 4,20 pontos percentuais para o MP e de 4,09 para as pesquisas). Constatou-se também que os preços dos contratos não são um simples reflexo dos resultados das pesquisas, o que indica que o mercado é capaz de agregar informações de diferentes fontes. Há potencial para o uso de MPs em eleições brasileiras, principalmente como complemento às metodologias de previsão mais tradicionais. Todavia, algumas limitações da ferramenta e possíveis restrições legais podem dificultar sua adoção. No tema economia, os erros foram ligeiramente maiores do que os obtidos com métodos alternativos. Logo, um MP aberto ao público geral, como foi o caso da BPrev, mostrou-se mais indicado para previsões eleitorais do que para previsões econômicas. Já no tema futebol, as previsões do MP foram melhores do que o critério do acaso, mas não houve diferença significante em relação a outro método de previsão baseado na análise estatística de dados históricos. No que diz respeito ao segundo objetivo, a análise da participação no MP aponta que motivações intrínsecas são mais importantes para explicar o uso do que motivações extrínsecas. Em ordem decrescente de relevância, os principais fatores que influenciam a adoção inicial da ferramenta são: prazer percebido, aprendizado percebido, utilidade percebida, interesse pelo tema das previsões, facilidade de uso percebida, altruísmo percebido e recompensa percebida. Os indivíduos com melhor desempenho no mercado são mais propensos a continuar participando. Isso sugere que, com o passar do tempo, o nível médio de habilidade dos participantes tende a crescer, tornando as previsões do MP cada vez melhores. Os resultados também indicam que a prática de incluir questões de entretenimento para incentivar a participação em outros temas é pouco eficaz. Diante de todas as conclusões, o MP revelou-se como potencial técnica de previsão em variados campos de investigação. / Prediction Market (PM) is a tool which uses the market price mechanism to aggregate information scattered in a large group of people, aiming at generating predictions about matters of interest. It is a low cost method, able to generate forecasts continuously and it does not require random samples. There are several applications for these markets and one of the main ones is the prognosis of election outcomes. This study analyzed empirical evidences on the effectiveness of Prediction Markets in Brazil, regarding forecasts about the outcomes of the general elections in the year of 2014, about economic indicators and about the results of the Brazilian Championship soccer games. The research had two main purposes: i) to develop and evaluate the performance of PMs in the Brazilian context, comparing their predictions to the alternative methods; ii) to explain what motivates people´s participation in PMs, especially when there is little or no interaction among participants and when the trades are made with a virtual currency (play-money). The study was made feasible by means of the creation of a prediction exchange named Bolsa de Previsões (BPrev), an online marketplace which operated for 61 days, from September to November, 2014, being open to the participation of any Brazilian Internet user. The 147 participants enrolled in BPrev made a total of 1,612 trades, with 760 on the election markets, 270 on economy and 582 on soccer. Two online surveys were also used to collect demographic data and users´ perceptions. The first one was applied to potential participants before BPrev launching (302 valid answers) and the second was applied only to the registered users after two-month experience in tool using (71 valid answers). Regarding the first purpose, the results suggest Prediction Markets to be feasible in the Brazilian context. On the election markets, the mean absolute error of PM predictions on the eve of the elections was of 3.33 percentage points whereas the one of the polls was of 3.31. Considering the whole period in which BPrev was running, the performance of both methods was also similar (PM mean absolute error of 4.20 percentage points and poll´s 4.09). Contract prices were also found as not being a simple reflection of poll results, indicating that the market is capable to aggregate information from different sources. There is scope for the use of PMs in Brazilian elections, mainly as a complement of the most traditional forecasting methodologies. Nevertheless, some tool limitations and legal restrictions may hinder their adoption. On markets about economic indicators, the errors were slightly higher than those obtained by alternative methods. Therefore, a PM open to general public, as in the case of BPrev, showed as being more suitable to electoral predictions than to economic ones. Yet, on soccer markets, PM predictions were better than the criterion of chance although there had not been significant difference in relation to other forecasting method based on the statistical analysis of historical data. As far as the second purpose is concerned, the analysis of people´s participation in PMs points out intrinsic motivations being more important in explaining their use than extrinsic motivations. In relevance descending order, the principal factors that influenced tool´s initial adoption are: perceived enjoyment, perceived learning, perceived usefulness, interest in the theme of predictions, perceived ease of use, perceived altruism and perceived reward. Individuals with better performance in the market are more inclined to continue participating. This suggests that, over time, participants´ average skill level tends to increase, making PM forecasts better and better. Results also indicate that the practice of creating entertainment markets to encourage participation in other subjects is ineffective. Ratifying all the conclusions, PM showed as being a prediction potential technique in a variety of research fields.