<p>In this thesis we study several inverse sampling procedures to test for homogeneity in a multivariate hypergeometric distribution. The procedures are finite population analogues of the procedures introduced in Panchapakesan et al. (1998) for the multinomial distribution. In order to develop some exact calculations for critical values not considered in Panchapakesan et al. we introduce some terminologies for target probabilities, transfer probabilities, potential target points, right intersection, and left union. Under the null and the alternative hypotheses, we give theorems to calculate the target and transfer probabilities, we then use these results to develop exact calculations for the critical values and powers of one of the procedures. We also propose a new approximate calculation. In order to speed up some of the calculations, we propose several fast algorithms for multiple summation.</p> <p>N >= 1680000, all the results are the same as those in the multinomial distribution.</p> <p>The computing results showed that the simulations agree closely with the exact results. For small population sizes the critical values and powers of the procedures are different from the corresponding multinomial procedures, but when</p> / Master of Science (MSc)

<p>In this thesis the problem of multitarget tracking in multistatic sensor networks is studied. This thesis focuses on tracking airborne targets by utilizing transmitters of opportunity in the surveillance region. Passive Coherent Location (PCL) system, which uses existing commercial signals (e.g., FM broadcast, digital TV) as the illuminators of opportunity for target tracking, is an emerging technology in air defence systems. PCL systems have many advantages over conventional radar systems such as low cost, covert operation and low vulnerability to electronic counter measures.</p> <p>One of another opportunistic signals available in the surveillance region is multipath signal. In this thesis, the multipath target return signals from distinct propagation modes that are resolvable by the receiver are exploited. When resolved multipath returns are not utilized within the tracker, i.e., discarded as clutter, potential information conveyed by the multipath detections of the same target is wasted. In this case, spurious tracks are formed using target-originated multipath measurements, but with an incorrect propagation mode assumption. Integrating multipath information into the tracker (and not discarding it) can help improve the accuracy of tracking and reduce the number of false tracks.</p> <p>In this thesis, these opportunistic measurements, i.e., commercial broadcast signals measurements in PCL tracking and resolvable multipath target return measurements in multipath assisted tracking are exploited. We give the optimal formulations for all of the above problems as well as the performance evaluations using PCRLB. Simulation results illustrate the performance of the algorithms.</p> / Doctor of Philosophy (PhD)

<p>Malnutrition and Anemia in children continue to be major public health challenges in most developing countries, particularly in Africa. Malnutrition and Anemia pervade all aspects of their health, growth, cognitive and social development. They lead to irreversible and lifelong effects that prevent children from realising their full potential. This study was designed to examine the prevalence and determinants of malnutrition and anemia in children under 5 years of age in the Ghanaian population. This research is based on data from the Ghana Demographic and Health Survey (GDHS) 2008, obtained from the Ghana Statistical Service (GSS). The survey is an extensive survey conducted using a stratified, two-stage cluster sampling design. The GDHS data contains a wealth of information on health, demographic, as well as socio-economic factors but is underutilised due to the complexity of the survey data. This study therefore stands out as one of the few that use the GDHS to investigate aspects of child health in Ghana. In this study, we perform subgroup analysis by disaggregating the data by age and gender specific subgroups and then by place of residence and region. This was in order to identify sub level estimates as national estimates have a high tendency of concealing true values and deviations from general trends. Also, subgroup analysis is very significant especially for resource allocation so as to minimize the likelihood of missing the target populations. We investigated associations between the three measurements of malnutrition; stunting, underweight and wasting and anemia (assessed by haemoglobin concentration) and the various risk factors using chi-square test to examine bivariate associations and chi-square trend test to examine linear trends in association. We identified the following variables to be significantly associated with all forms of malnutrition and/or anemia: age of child, mother’s education, financial status and place of residence. Other factors that were identified to be associated with some form of malnutrition and/or anemia include duration of breastfeeding, source of drinking water, mother’s occupation and currently breastfeeding. In view of the high rate of malnutrition, approximately 36% (33.6−37.6) and the alarming prevalence of anemia, 78% (76.7 − 80.2) in children in Ghana, particularly among those less than 2 years old, and the grave consequences on their cognitive and behavioral development even in later years, there is an urgent need for effective and efficient public health interventions.</p> / Master of Science (MSc)

Within NASA's Air Traffic Management Technology Demonstration # 1 (ATD-1), Interval Management (IM) is a flight deck tool that enables pilots to achieve or maintain a precise in-trail spacing behind a target aircraft. Previous research has shown that violations of aircraft spacing requirements can occur between an IM aircraft and its surrounding non-IM aircraft when it is following a target on a separate route. This research focused on the experimental design and analysis of a deterministic computer simulation which models our airspace configuration of interest. Using an original space-filling design and Gaussian process modeling, we found that aircraft delay assignments and wind profiles significantly impact the likelihood of spacing violations and the interruption of IM operations. However, we also found that implementing two theoretical advancements in IM technologies can potentially lead to promising results.

When the variance of a single population needs to be assessed, the well-known chi-squared test of variance is often used but relies heavily on its normality assumption. For non-normal populations, few alternative tests have been developed to conduct left tailed hypothesis tests of variance. This thesis outlines a method for generating new test statistics using a saddlepoint approximation. Several novel test statistics are proposed. The type-I error rates and power of each test are evaluated using a Monte Carlo simulation study. One of the proposed test statistics, R_gamma2, controls type-I error rates better than existing tests, while having comparable power. The only observed limitation is for populations that are highly skewed with heavy-tails, for which all tests under consideration performed poorly.

<div>Prediction of player performance is a key component in the construction of baseball team rosters. Traditionally, the problem of predicting seasonal plate appearance outcomes has been approached univariately. That is, focusing on each outcome separately rather than jointly modeling the collection of outcomes. More recently, there has been a greater emphasis on joint modeling, thereby accounting for the correlations between outcomes. However, most of these state of the art prediction models are the proprietary property of teams or industrial sports entities and so little is available in open publications.</div><div><br></div><div>This dissertation introduces a joint modeling approach to predict seasonal plate appearance outcome vectors using a mixed-effects multinomial logistic-normal model. This model accounts for positive and negative correlations between outcomes both across and within player seasons. It is also applied to the important, yet unaddressed, problem of predicting performance for players moving between the Japanese and American major leagues.</div><div><br></div>This work begins by motivating the methodological choices through a comparison of state of the art procedures followed by a detailed description of the modeling and estimation approach that includes model t assessments. We then apply the method to longitudinal multinomial count data of baseball player-seasons for players moving between the Japanese and American major leagues and discuss the results. Extensions of this modeling framework to other similar data structures are also discussed.<br>

Enquanto a Administração de Empresas evoluiu muito no último século e trouxe vasto ferramental aos gestores de empresas, o tema da Responsabilidade Social Empresarial (RSE) não acompanhou essa evolução e ainda não dispõe de conceitos sólidos e ferramental de apoio aos gestores. Isso justifica o presente estudo, que objetiva identificar, empiricamente, o comportamento das empresas que operam no Brasil, referente aos seus investimentos em ações de RSE e suas relações com o Desempenho Financeiro (DF), com base na Receita Líquida (RL) e no Resultado Operacional (RO). A partir de uma amostra de 2064 Balanços Sociais padrão IBASE (BS) de 378 empresas, no período entre 1996 e 2010, o estudo buscou resposta a oito perguntas de pesquisa e encontrou comportamentos estatisticamente significativos em todas elas. Os resultados indicam que existe relacionamento direto entre a RL e os investimentos em RSE. Existe também um relacionamento direto entre o RO-Positivo e os investimentos em RSE. Nos casos em que o RO é negativo, o relacionamento com os investimentos em RSE está associado ao valor absoluto do RO-Negativo, o que pode ser uma relação dependente da RL ou do porte da empresa. O setor de atuação das empresas é um fator que segmenta comportamentos característicos das empresas e nem todas as turbulências conjunturais nacionais e internacionais impactam e influenciam as decisões de investimentos em RSE e o DF das empresas de forma semelhante. Os modelos matemáticos que relacionam a RL com os investimentos em RSE têm melhor capacidade explicativa que os modelos correspondentes que relacionam o RO a esses mesmos investimentos, sendo que o setor de atuação é um diferenciador significativo. Não foram encontradas diferenças significativas na qualidade explicativa dos modelos matemáticos que consideraram o DF do ano-base e do ano anterior em relação às decisões de investimentos em RSE e, mais, a composição do portfólio de investimento em RSE varia em função do setor e do ano de publicação dos BSs. / While Business Management was much developed during the last hundred years and accumulated a lot of management tools to managers of companies, the theme of Corporate Social Responsibility (CSR) has only received tangential attention and does not yet have solid concepts and tools to support managers. This lack of similar evolution justifies the present study, which aims to identify, empirically, the behavior of companies operating in Brazil, related to their investments in activities of CSR and its relations with Financial Performance (FP), based on Net Income (NI) and Operational Results (OR). From a sample of 2064 IBASE Social Accounting Balances (SAB) of 378 companies between 1996 and 2010, the study sought to answer eight research questions and found statistically significant behavior in all of them. The results indicate that there is direct relationship between the NI and investments in CSR. There is also a direct relationship between the ORPositive and investments in CSR. When OR is negative, the relationship between CSR investment is associated with the absolute value of OR-negative, which may be a dependent relationship of NI or size of the company. The business sector is a factor that segments the characteristic behaviors of companies, and not all national and international economic turmoil impact and influence investment decisions in CSR and FP of firms with the same magnitude. The mathematical models that relate the NI with investments in CSR have better explanatory power than models that relate the OR corresponding to such investments, and the sector of activity is a significant differentiator. There were no significant differences in the explanatory quality of mathematical models that considered the FP for the base year and the year before, in relation to decisions on investments in CSR,, and the composition of the investment in CSR portfolio varies by sector and year of publication of SABs.

We consider discrete and continuous symmetric random variables X taking values in [0; 1], and thus having expected value 1/2. The main thrust of this investigation is to study the correlation between the variance, Var(X) of X and the value of the expected maximum E(Mn) = E(X1,...,Xn) of n independent and identically distributed random variables X1,X2,...,Xn, each distributed as X. Many special cases are studied, some leading to very interesting alternating sums, and some progress is made towards a general theory.

Longitudinal data arise when individuals are measured several times during an ob- servation period and thus the data for each individual are not independent. There are several ways of analyzing longitudinal data when different treatments are com- pared. Multilevel models are used to analyze data that are clustered in some way. In this work, multilevel models are used to analyze longitudinal data from a case study. Results from other more commonly used methods are compared to multilevel models. Also, comparison in output between two software, SAS and R, is done. Finally a method consisting of fitting individual models for each individual and then doing ANOVA type analysis on the estimated parameters of the individual models is proposed and its power for different sample sizes and effect sizes is studied by simulation.

Protein identification using tandem mass spectrometry (MS/MS) has proven to be an effective way to identify proteins in a biological sample. An observed spectrum is constructed from the data produced by the tandem mass spectrometer. A protein can be identified if the observed spectrum aligns with the theoretical spectrum. However, data generated by the tandem mass spectrometer are affected by errors thus making protein identification challenging in the field of proteomics. Some of these errors include wrong calibration of the instrument, instrument distortion and noise. In this thesis, we present a pre-processing method, which focuses on the removal of noisy data with the hope of aiding in better identification of proteins. We employ the method of binning to reduce the number of noise peaks in the data without sacrificing the alignment of the observed spectrum with the theoretical spectrum. In some cases, the alignment of the two spectra improved.