This thesis presents a comparison of correlation methods in risk analysis. A theoretical solution is given to the correlation problem along with a discussion of each method. Each method is compared to a developed test case and two other cost projects. Restrictions on correlation coefficients are also given followed by the advantages and disadvantages of each method. / Master of Science

New methods for testing hypotheses in paired-comparison experiments are presented in this dissertation. The methods are developed on the basis of a very general mathematical model and they are, in general, quite easy to employ. Two tests of the null hypothesis that all treatments have equal stimuli, against its general alternative, are proposed. One test is for the case in which it is assumed prior to the experiment that no interaction will take place between repetitions and preference probabilities (the probabilities of the possible comparison preferences). The other test is for the case in which the above assumption cannot be made. The number of times a treatment is preferred is called its score. For the “no interaction" case, the test procedure is based on a test statistic that is a function D of the corrected sum of squares of the treatment scores. In the other case, the value of D is calculated for each group of homogeneous repetitions and then the values are summed to give the new test statistic. It is established that a X²-approximation may be used to determine the critical value of the test statistic for experiments outside the range of the tabled distributions. This test procedure is shown to be simpler than other approximate tests and, in general, at least as accurate with respect to errors of the first kind. It is shown that the two test methods discussed above may be extended to ranking experiments in balanced incomplete block designs with more than two treatments per block. To test the null hypothesis of no interaction between preference probabilities and repetitions, against its general alternative, a test method based on the theory of X² homogeneity tests is introduced. Means are presented for testing whether (1) a particular treatment is better than the average of the treatment stimuli; (2) two particular treatment stimuli are not equal; and (3) the treatment receiving the highest score is better than the average. The three test procedures are based essentially on the binomial distribution of the treatment scores under the null hypothesis. In each case, the test procedure is conservative. A procedure analogous to Tukey's test based on allowances is developed to test the null hypothesis of equal treatment stimuli and to separate the significantly different treatment scores when it rejects the null hypothesis. A method for judging contrasts of treatment scores similar to Scheffe's (1953) method for judging contrasts in the analysis of variance is proposed. The test method based on D, mentioned earlier, is used in place of the F-test employed in the Scheffe method. The use of paired-comparison experiments to test factorial effects is discussed and a test method based on orthogonal contrasts of the treatment scores is suggested. Because of correlations that arise, it is necessary to restrict this method to cases in which the only factors that are allowed to appear at more than two levels are those that will not interact with the other factors in the experiment. The test methods are illustrated through application on the data from two paired-comparison experiments. / Ph. D.

This dissertation is concerned with the problem of the exact pole-placement by minimum control effort using state and output feedback for linear multivariable systems. The novelty of the design lies in obtaining a direct transformation of the system matrices into a modified controllable canonical form. Two realizations are identified, and the algorithms to obtain them are derived. In both cases, the transformation matrix has some degrees of freedom by tuning a scalar or a set of scalars within the matrix. These degrees of freedom are utilized in the solution to reduce further the norm of the state feedback matrix. Then the pole-placement problem is solved by minimizing a certain functional, subject to a set of specified constraints. A non-canonical form approach to the problem is also proposed, where it was only necessary to transform the input matrix to a special form. The transformation matrix, in this method, has larger degrees of freedom which can be utilized in the solution. Moreover, a new pole-placement method based on the non-canonical approach is derived. The solution, in this method, was made possible by solving the Lyapunov matrix equation. Finally, an iterative algorithm for pole-placement by output feedback is extended so as to obtain an output feedback matrix with a small norm. The extension has been accomplished by applying the successive pole shifting method. Two schemes for the pole shifting are proposed. The first is to successively shift the poles through straight paths starting from the open loop poles and ending at the desired poles, whereas the second scheme shifts the poles according to a successive change of their characteristic polynomial coefficients. / Ph. D. / incomplete_metadata

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The problem of the study was related to the asymptotic and relative efficiencies of the conventional biserial correlation coefficients and the two modified biserial correlation coefficients proposed by Brogden (1) and Lord-Clemans (2; 15). These were determined under some selected cutting points (p), and various sizes of samples (n) randomly drawn from the; simulated bivariate populations of four different shapes—normal, lognormal, double exponential, and the contaminated normal, and of various degrees in population parameter (p).

A research report submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, in partial fulfilment of the requirements for the degree of Master of Science in Engineering. Johannesburg, 2017 / The period from 2006 to 2015 was a turbulent one for mining companies. The end of the 2000s commodity super cycle resulted in all-time high market values for most commodity based companies, followed by a rapid decline in value with the onset of the Global Financial Crisis in 2008 and a similar rapid recovery following this. Whilst much of this change in value was driven by commodity prices, the inconsistent performance between companies suggests that there are other factors affecting mining company value. To determine the key drivers of company value, four diversified and international mining companies which represent close to 50% of the 2006 industry revenue were selected for analysis. These were Anglo American, BHP Billiton, Rio Tinto and CVRD-Vale. Financial and production data was collected to analyse different potential value drivers. Because of its suitability for comparison of company value, the market based valuation approach was selected as the company valuation technique. Enterprise value (EV) was the metric used for company value since this provides a measure of the real market value of a firm as a whole business. Eight potential value drivers, which include production output, commodity price, revenue, EBITDA margin, EBITDA multiple, gearing ratio, net debt to EBITDA ratio and ROCE, were selected for analysis. Each potential value driver was tracked against EV to determine if there was any correlation between the value driver and EV. Also, the Pearson correlation method was used to determine correlation between each potential value driver and EV. Production output and commodity price in isolation were found not to drive company value. However, when combined to calculate revenue, had a very high correlation to EV with an average Pearson coefficient of 0.8. EBITDA multiple was also found to be a key driver of company value, with this metric closely aligned to revenue (Pearson coefficient of 0.6). The two debt metrics, gearing ratio and net debt to EBITDA were found to only have a correlation to EV in times of declining commodity prices and revenue. EBITDA margin and ROCE were found to have no correlation to EV and as such were not considered to be key drivers of company value. Mining companies must ensure that they focus on the correct value drivers to ensure those they influence do impact the company value. / MT 2017

Orientador: Josineudson Augusto II Vasconcelos Silva / Coorientador: Lenira El Faro Zadra / Banca: Danísio Padro Munari / Banca: Rúsbel Raul Aspilcueta Borquis / Resumo: O desempenho medido por características de produção de leite e de eficiência reprodutiva são os principais critérios de seleção nos rebanhos leiteiros devido às consequências diretas na rentabilidade econômica do sistema. O objetivo deste trabalho foi identificar as variáveis que representem a maior parte da variação fenotípica e genética, além de estimar os parâmetros genéticos de características de produção e reprodução. Foram analisados registros de 5.217 matrizes da raça Holandesa utilizando análise de componentes principais (ACP) e análise de fatores (AF). As características avaliadas foram: produção de leite aos 305 dias de lactação (P305), produção de leite por dia de intervalo de partos (PLIEP) e pico de lactação (PICO), intervalo da data do parto ao primeiro cio (I1C), intervalo da data do parto a última cobertura (IUC), intervalo de partos (IP) e duração da gestação (DG). A estrutura de associação das características foi verificada utilizando os métodos ACP e AF para extrair novas variáveis a partir da matriz de correlação dos fenótipos por meio do software estatístico SAS®. Os resultados indicaram que ACP e AF extraíram três e quatro variáveis latentes retendo 81,5 e 88,9% da variação total dos dados, respectivamente. As características que tiveram maior participação nos componentes e fatores selecionados foram P305, PLIEP, PICO, IUC e IP. A característica DG apresentou independência frente ao conjunto de variáveis avaliadas. Parâmetros genéticos foram estimados ut... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The main causes of discard in dairy herds are the milk production and the reproductive efficiency traits due to direct consequences on economic profitability of the system. These two groups of characteristics are interconnected, occurring correlated response when selected some of them. The aim of this study was to evaluate the structure of phenotypic and genetic associations in addition to estimate genetic parameters of production and reproduction traits. Records of 5,217 Holstein cows were analyzed using principal component analysis (PCA) and factor analysis (FA). The traits studied were: 305-day accumulative milk yield (Y305), milk yield per day of calving interval (MYCI) and peak yield (PY), interval between calving and first estrus (CFE) interval between calving and last service (CLS), calving interval (CI), and gestation length (GL).The association structure of the traits was verified using the ACP and AF methods to extract new variables from the phenotypes correlation matrix using statistical software SAS®. The results indicate that ACP and AF managed to extract three and four latent variables explained 81 and 88.9% of the total variance of the dataset, respectively. The principal component analysis was more efficient than the analysis of factors, get summarize the information in fewer latent variables. Genetic parameters were estimated using six different models: standard multi-trait model and five reduced rank models fitting the first 2, 3, 4, 5 and 6 genetic principa... (Complete abstract click electronic access below) / Mestre

Orientador: Gustavo Vitti Môro / Banca: Maria Elisa Ayres Guidetti Zagatto Paterniani / Banca: Ivana Marino Bárbaro Torneli / Banca: Rinaldo César de Paula / Banca: Dilermando Perecin / Resumo: O milho-pipoca nacional apresenta baixa variabilidade genética e o desenvolvimento de linhagens avançadas e novas cultivares com alta produtividade de grãos (PG) e capacidade de expansão (CE) é dependente da determinação precisa de grupos heteróticos e do conhecimento das associações entre as principais características de importância para a cultura. O objetivo deste trabalho foi realizar análise dialélica e estimar a correlação entre as principais características em populações oriundas de linhagens S3 de milho-pipoca. Para avaliação da capacidade combinatória foram obtidos 36 híbridos e seus recíprocos, os quais foram avaliados em delineamento de blocos casualizados com 72 tratamentos e duas repetições em dois anos, sendo avaliada a PG e CE. Para avaliação da correlação entre as características foi utilizado 41 genótipos dentre os híbridos e recíprocos obtidos que foram avaliados em blocos casualizados para três amostras de 50 grãos de cada parcela de cada repetição: comprimento do grão (CG), espessura do grão (EG), largura do grão (LG), diâmetro do grão (DG) massa de 50 grãos (MG) e CE. Foram estimados a capacidade geral e especifica de combinação, o efeito recíproco e materno, o coeficiente de correlação de Pearson, foi realizada análise de trilha, modelos de regressão simples e redes bayesianas. Os efeitos não aditivos dos genes foram os mais importantes no controle genético tanto da PG como da CE, indicando situação favorável para a exploração de híbridos nos programas d... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The Brazilian popcorn has low genetic variability and the development of advanced lines and new cultivars with high grain yield (GY) and expansion volume (EV) is dependent on the accurate determination of heterotic groups and knowledge of associations between the main traits. The aim of this study was apply diallel analysis and correlation coefficient among the main traits from S3 lines populations of popcorn. The 36 hybrids and its reciprocals were evaluated in a randomized complete block design (RCBD) with 72 treatments and two replications in two years and GY and EV were evaluated. At the same time, from 41 hybrids of popcorn were evaluated in a RCBD design for three samples of 50 kernel from each plot: grain length (GL), grain thickness (GT), grain width (GW) of grain diameter (GD) mass of 50 grains (MG) and EV. It was estimated the general e specific combining ability, as well as the reciprocal and maternal effect, Pearson correlation coefficient, path analysis, simple regression models and Bayesian networks. The non-additive effects of genes were the most important in the genetic control of GY and EV indicating favorable situation to produce hybrids. The reciprocal effect is mainly due to non-maternal effects. The use of synthetic populations from S3 lines can be an alternative to increase the genetic variability for GY and EV in popcorn breeding programs. It was detected negative correlation between EV and the traits, except for GD, corroborating the regression models. Path analysis indicated that MG has direct and positive effect on the EV and the negative correlation observed is mainly due to the indirect effects by GW and GT. Bayesian networks detected no direct association between the kernel size and indicated that GT is the only measure that can influence the flake size of popcorn / Doutor

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1981. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Includes bibliographical references. / by David Matthew DeLonga; Ensign, USN. / M.S.

Keywords: Latent variables, Ordered categorical data, Unordered categorical data, Nonignorable missing data, Maximum likelihood approach, Bayesian approach. / Structural equation models (SEMs) have been widely applied to examine interrelationships among latent and observed variables in behavioral, psychological, and medical research. Motivated by the fact that correlated ordered and unordered categorical variables are frequently encountered in practical applications, a nonlinear SEM that accommodates fixed covariates, mixed continuous, ordered categorical, and unordered categorical variables is proposed. Maximum likelihood methods for estimation and model comparison are discussed. Besides, missing data are frequently encountered in practical researches; a lot of attention has been devoted to analyze various SEMs with missing data. Bayesian analysis, including parameter estimate and model comparison, of a nonlinear SEM with mixed continuous, ordered and unordered categorical variables, and nonignorable missing entries is also considered in the thesis. Simulation studies are conducted to reveal the performance of the proposed methods. Moreover, we apply our methodologies to analyze the real-life data set about cardiovascular disease. As none of the existing SEMs can simultaneously accommodate fixed covariates, mixed continuous, ordered and unordered categorical data, and missing data, this thesis offers a novel SEM to cope with more complex practical problems and develop maximum likelihood and Bayesian methods for obtaining results in estimation and model comparison. / Cai, Jingheng. / Advisers: Sik-Yum Lee; Xin-Yuan Song. / Source: Dissertation Abstracts International, Volume: 70-06, Section: B, page: 3584. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 76-82). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.