The hyperbolic relationship between power output and endurance time can be measured using all-out exercise. The aims of this thesis were to (i) assess whether the all-out test could be used under novel testing protocols to provide valid power-duration (P-D) parameter estimates; and (ii) attempt to elucidate the likely physiological composition of the P-D curvature constant. All-out tests were initiated from moderate-(M), heavy-(H) and severe-(S2 & S4) intensity ‘baselines’ (chapter 4). The work performed above end power (WEP) was not different to control under M or H conditions but was significantly, predictably reduced under the S2 & S4 conditions (control: 16.3 ± 2.2; M: 17.2 ± 2.4; H: 15.6 ± 2.3 kJ, P > 0.05; S2: 11.5 ± 2.5; S4: 8.9 ± 2.2 kJ, P < 0.05). The 3-min all-out test end power (EP) parameter was unaffected. Muscle glycogen may form part of the WEP. Type I (T1) and type II (T2) muscle fibres were depleted of their glycogen content prior to the all-out test (chapter 5). EP and WEP were unaffected by either T1 or T2 glycogen depletion. The all-out tests was conducted under hypoxic conditions alongside the criterion assessment of the P-D relationship (chapter 6). Normobaric moderate hypoxia caused a reduction in CP (control: 175 ± 25; hypoxia: 132 ± 17 W, P < 0.001) without affecting W′ (control: 13.2 ± 2.2; hypoxia: 12.3 ± 2.7 kJ, P > 0.05). The 3-min all-out test provided EP and WEP estimates, which did not differ to CP and W′ (control: EP 172 ± 30 W, WEP 12.0 ± 2.6 kJ; hypoxia EP 134 ± 23 W, WEP 12.5 ± 1.4 kJ, P > 0.05) providing the ergometer resistance was adjusted for the hypoxic conditions. Furthermore, a significant negative relationship was observed between %∆ ( O2peak – CP) and %∆W′ (r = -0.83, P < 0.001); thus, W′ may represent the relative ‘size’ of the severe-intensity domain. The all-out test was used to track training-induced changes in P-D parameters in response to 6-weeks of sprint or endurance training (chapter 7). EP & WEP were differently altered compared to CP and W′ following sprint training (CP 12 ± 9; EP -0 ± 9 % change; W′ -5 ± 25; WEP 11 ± 15 % change). The all-out test reliably tracked changes in CP and W′ following endurance training. In conclusion, the all-out test provides reliable EP and WEP values. Its validity is acceptable, but is perhaps affected by exercise training that is specific to the execution of the test. The W′ appears to be determined, to a large extent, by the relative size of the severe-intensity domain.

O objetivo deste trabalho é desenvolver e propor um novo método para o planejamento de redes geodésicas. O planejamento (ou pré-análise) de uma rede geodésica consiste em planejar (ou otimizar) a rede, de modo que a mesma atenda a critérios de qualidade pré-estabelecidos de acordo com os objetivos do projeto, como precisão, confiabilidade e custos. No método aqui proposto, os critérios a serem considerados na etapa de planejamento são os níveis de confiabilidade e homogeneidade mínimos aceitáveis para as observações; a acurácia posicional dos vértices, considerando tanto os efeitos de precisão quanto os (possíveis) efeitos de tendência, segundo ainda um determinado nível de confiança; o número de outliers não detectados máximo admissível; e o poder do teste mínimo do procedimento Data Snooping (DS) no cenário n-dimensional, isto é, considerando todas as observações (testadas individualmente). De acordo com as classificações encontradas na literatura, o método aqui proposto consiste em um projeto combinado, solucionado por meio do método da tentativa e erro, além de apresentar alguns aspectos inéditos em seus critérios de planejamento. Para demonstrar a sua aplicação prática, um exemplo numérico de planejamento de uma rede GNSS (Global Navigation Satellite System – Sistema Global de Navegação por Satélite) é apresentado e descrito. Os resultados obtidos após o processamento dos dados da rede GNSS foram concordantes com os valores estimados na sua etapa de planejamento, ou seja, o método aqui proposto apresentou desempenho satisfatório na prática. Além disso, também foram investigados como os critérios pré-estabelecidos, a geometria/configuração da rede geodésica e a precisão/correlação inicial das observações podem influenciar nos resultados obtidos na etapa de planejamento, seguindo o método aqui proposto. Com a realização destes experimentos, dentre outras conclusões, verificou-se que todo os critérios de planejamento do método aqui proposto estão intrinsecamente interligados, pois, por exemplo, uma baixa redundância conduz a um valor relativamente mais alto para a componente de precisão, e consequentemente, um valor relativamente mais baixo para a componente de tendência (mantendo a acurácia final constante), o que também conduz a um poder do teste mínimo nos cenários unidimensional e n-dimensional significativamente mais baixos. / The aim of this work is to develop and propose a new method for the design of geodetic networks. Design (planning or pre-analysis) of a geodetic network consists of planning (or optimizing) the network so that it follows the pre-established quality criteria according to the project objectives, such as accuracy, reliability and costs. In the method proposed here, the criteria to be considered in the planning stage are the minimum acceptable levels of reliability and homogeneity of the observations; the positional accuracy of the points considering both the effects of precision and the (possible) effects of bias (according to a given confidence level); the maximum allowable number of undetected outliers; and the minimum power of the test of the Data Snooping procedure (DS) in the n-dimensional scenario, i.e., considering all observations (individually tested). According to the classifications found in the literature, the method proposed here consists of a combined project, solved by means of trial and error approach, and presents some new aspects in their planning criteria. To demonstrate its practical application, a numerical example of a GNSS (Global Navigation Satellite System) network design is presented and described. The results obtained after processing the data of the GNSS network were found in agreement with the estimated values in the design stage, i.e., the method proposed here showed satisfactory performance in practice. Moreover, were also investigated as the pre-established criteria, the geometry/configuration of the geodetic network, and the initial values for precision/correlation of the observations may influence the results obtained in the planning stage, following the method proposed here. In these experiments, among other findings, it was found that all the design criteria of the method proposed here are intrinsically related, e.g., a low redundancy leads to a relatively higher value for the precision component, and consequently to a relatively lower value for the bias component (keeping constant the final accuracy), which also leads to a minimum power of the test significantly lower in the one-dimensional and the n-dimensional scenarios.

O objetivo deste trabalho é desenvolver e propor um novo método para o planejamento de redes geodésicas. O planejamento (ou pré-análise) de uma rede geodésica consiste em planejar (ou otimizar) a rede, de modo que a mesma atenda a critérios de qualidade pré-estabelecidos de acordo com os objetivos do projeto, como precisão, confiabilidade e custos. No método aqui proposto, os critérios a serem considerados na etapa de planejamento são os níveis de confiabilidade e homogeneidade mínimos aceitáveis para as observações; a acurácia posicional dos vértices, considerando tanto os efeitos de precisão quanto os (possíveis) efeitos de tendência, segundo ainda um determinado nível de confiança; o número de outliers não detectados máximo admissível; e o poder do teste mínimo do procedimento Data Snooping (DS) no cenário n-dimensional, isto é, considerando todas as observações (testadas individualmente). De acordo com as classificações encontradas na literatura, o método aqui proposto consiste em um projeto combinado, solucionado por meio do método da tentativa e erro, além de apresentar alguns aspectos inéditos em seus critérios de planejamento. Para demonstrar a sua aplicação prática, um exemplo numérico de planejamento de uma rede GNSS (Global Navigation Satellite System – Sistema Global de Navegação por Satélite) é apresentado e descrito. Os resultados obtidos após o processamento dos dados da rede GNSS foram concordantes com os valores estimados na sua etapa de planejamento, ou seja, o método aqui proposto apresentou desempenho satisfatório na prática. Além disso, também foram investigados como os critérios pré-estabelecidos, a geometria/configuração da rede geodésica e a precisão/correlação inicial das observações podem influenciar nos resultados obtidos na etapa de planejamento, seguindo o método aqui proposto. Com a realização destes experimentos, dentre outras conclusões, verificou-se que todo os critérios de planejamento do método aqui proposto estão intrinsecamente interligados, pois, por exemplo, uma baixa redundância conduz a um valor relativamente mais alto para a componente de precisão, e consequentemente, um valor relativamente mais baixo para a componente de tendência (mantendo a acurácia final constante), o que também conduz a um poder do teste mínimo nos cenários unidimensional e n-dimensional significativamente mais baixos. / The aim of this work is to develop and propose a new method for the design of geodetic networks. Design (planning or pre-analysis) of a geodetic network consists of planning (or optimizing) the network so that it follows the pre-established quality criteria according to the project objectives, such as accuracy, reliability and costs. In the method proposed here, the criteria to be considered in the planning stage are the minimum acceptable levels of reliability and homogeneity of the observations; the positional accuracy of the points considering both the effects of precision and the (possible) effects of bias (according to a given confidence level); the maximum allowable number of undetected outliers; and the minimum power of the test of the Data Snooping procedure (DS) in the n-dimensional scenario, i.e., considering all observations (individually tested). According to the classifications found in the literature, the method proposed here consists of a combined project, solved by means of trial and error approach, and presents some new aspects in their planning criteria. To demonstrate its practical application, a numerical example of a GNSS (Global Navigation Satellite System) network design is presented and described. The results obtained after processing the data of the GNSS network were found in agreement with the estimated values in the design stage, i.e., the method proposed here showed satisfactory performance in practice. Moreover, were also investigated as the pre-established criteria, the geometry/configuration of the geodetic network, and the initial values for precision/correlation of the observations may influence the results obtained in the planning stage, following the method proposed here. In these experiments, among other findings, it was found that all the design criteria of the method proposed here are intrinsically related, e.g., a low redundancy leads to a relatively higher value for the precision component, and consequently to a relatively lower value for the bias component (keeping constant the final accuracy), which also leads to a minimum power of the test significantly lower in the one-dimensional and the n-dimensional scenarios.

O objetivo deste trabalho é desenvolver e propor um novo método para o planejamento de redes geodésicas. O planejamento (ou pré-análise) de uma rede geodésica consiste em planejar (ou otimizar) a rede, de modo que a mesma atenda a critérios de qualidade pré-estabelecidos de acordo com os objetivos do projeto, como precisão, confiabilidade e custos. No método aqui proposto, os critérios a serem considerados na etapa de planejamento são os níveis de confiabilidade e homogeneidade mínimos aceitáveis para as observações; a acurácia posicional dos vértices, considerando tanto os efeitos de precisão quanto os (possíveis) efeitos de tendência, segundo ainda um determinado nível de confiança; o número de outliers não detectados máximo admissível; e o poder do teste mínimo do procedimento Data Snooping (DS) no cenário n-dimensional, isto é, considerando todas as observações (testadas individualmente). De acordo com as classificações encontradas na literatura, o método aqui proposto consiste em um projeto combinado, solucionado por meio do método da tentativa e erro, além de apresentar alguns aspectos inéditos em seus critérios de planejamento. Para demonstrar a sua aplicação prática, um exemplo numérico de planejamento de uma rede GNSS (Global Navigation Satellite System – Sistema Global de Navegação por Satélite) é apresentado e descrito. Os resultados obtidos após o processamento dos dados da rede GNSS foram concordantes com os valores estimados na sua etapa de planejamento, ou seja, o método aqui proposto apresentou desempenho satisfatório na prática. Além disso, também foram investigados como os critérios pré-estabelecidos, a geometria/configuração da rede geodésica e a precisão/correlação inicial das observações podem influenciar nos resultados obtidos na etapa de planejamento, seguindo o método aqui proposto. Com a realização destes experimentos, dentre outras conclusões, verificou-se que todo os critérios de planejamento do método aqui proposto estão intrinsecamente interligados, pois, por exemplo, uma baixa redundância conduz a um valor relativamente mais alto para a componente de precisão, e consequentemente, um valor relativamente mais baixo para a componente de tendência (mantendo a acurácia final constante), o que também conduz a um poder do teste mínimo nos cenários unidimensional e n-dimensional significativamente mais baixos. / The aim of this work is to develop and propose a new method for the design of geodetic networks. Design (planning or pre-analysis) of a geodetic network consists of planning (or optimizing) the network so that it follows the pre-established quality criteria according to the project objectives, such as accuracy, reliability and costs. In the method proposed here, the criteria to be considered in the planning stage are the minimum acceptable levels of reliability and homogeneity of the observations; the positional accuracy of the points considering both the effects of precision and the (possible) effects of bias (according to a given confidence level); the maximum allowable number of undetected outliers; and the minimum power of the test of the Data Snooping procedure (DS) in the n-dimensional scenario, i.e., considering all observations (individually tested). According to the classifications found in the literature, the method proposed here consists of a combined project, solved by means of trial and error approach, and presents some new aspects in their planning criteria. To demonstrate its practical application, a numerical example of a GNSS (Global Navigation Satellite System) network design is presented and described. The results obtained after processing the data of the GNSS network were found in agreement with the estimated values in the design stage, i.e., the method proposed here showed satisfactory performance in practice. Moreover, were also investigated as the pre-established criteria, the geometry/configuration of the geodetic network, and the initial values for precision/correlation of the observations may influence the results obtained in the planning stage, following the method proposed here. In these experiments, among other findings, it was found that all the design criteria of the method proposed here are intrinsically related, e.g., a low redundancy leads to a relatively higher value for the precision component, and consequently to a relatively lower value for the bias component (keeping constant the final accuracy), which also leads to a minimum power of the test significantly lower in the one-dimensional and the n-dimensional scenarios.

Thesis (MComm (Statistics and Actuarial Science))--Stellenbosch University, 2008. / The goodness-of- t of a statistical model describes how well it ts a set of observations. Measures of goodness-of- t typically summarize the discrepancy between observed values and the values expected under the model in question. Such measures can be used in statistical hypothesis testing, for example to test for normality, to test whether two samples are drawn from identical distributions, or whether outcome frequencies follow a speci ed distribution. Goodness-of- t for copulas is a special case of the more general problem of testing multivariate models, but is complicated due to the di culty of specifying marginal distributions. In this thesis, the goodness-of- t test statistics for general distributions and the tests for copulas are investigated, but prior to that an understanding of copulas and their properties is developed. In fact copulas are useful tools for understanding relationships among multivariate variables, and are important tools for describing the dependence structure between random variables. Several univariate, bivariate and multivariate test statistics are investigated, the emphasis being on tests for normality. Among goodness-of- t tests for copulas, tests based on the probability integral transform, Rosenblatt's transformation, as well as some dimension reduction techniques are considered. Bootstrap procedures are also described. Simulation studies are conducted to rst compare the power of rejection of the null hypothesis of the Clayton copula by four di erent test statistics under the alternative of the Gumbel-Hougaard copula, and also to compare the power of rejection of the null hypothesis of the Gumbel-Hougaard copula under the alternative of the Clayton copula. An application of the described techniques is made to a practical data set.

Diploma thesis is focused on comparison of small punch test results and tensile test results. For experiments were chosen steel P91, 10Ch2MFA, 20CrNi2MoV, 11 416 and 42 2707. These steel are used in nuclear power engineering, or they were developed for this purpose. Basic mechanical characteristics, namely ultimate tensile stress and yield stress, were evaluated from small punch test records of observed materials. This is done via convenient correlation relationships. Obtained values were compared with values obtained by conventional tensile tests. There are mentioned own suggested correlation relationships and comparison of temperature curves gained from small punch test and tensile test in the thesis. Assessment of microstructure of observed materials and analysis of fracture surfaces was provided as well. It was found out, that for assessing basic mechanical characteristics (ultimate tensile stress and yield stress) is the best to suggest own correlation relationships, instead of using universal relationships from literature. The fracture mechanism of all types of assessed steel was ductile in entire temperature range (up to -40 °C).

Conselho Nacional de Desenvolvimento Científico e Tecnológico / The likelihood ratio test for independence between two groups of variables allows us to identify whether there is a dependency relationship between two groups of variables, ie, if the covariance between the two groups are zero. This test assumes normality multivariate data, which limits its application, in many studies of agronomic area, times when you need use, for example, the canonical correlation analysis. The objective of this study is to evaluate the type I error and power of the likelihood ratio test (LRT) for independence between two groups of variables in different scenarios, consisting of combinations of: sample sizes 16, 40 number of combinations of two variables groups, and nine degrees of correlation between variables in matrices (for power); multivariate normal distribution under normal and contaminated, as well as compare the different scenarios, two formulas for calculating the test statistic. Thus, were evaluated the effect of 640 and 5760 scenarios on rates of type I error and power, respectively, in each one of probability distributions and formulas. The assessment of performance of LRT was performed through computational simulation by Monte Carlo method, using 2000 simulations in each of the scenarios generated. In multivariate normal situation: when the number of variables is large (p = 24), the LRT for independence between two groups of variables, controls the type I error rates and has high power in sample sizes greater than 100 and 500, with use of formulas for small and large samples, respectively; and, for sample sizes small (n = 25, 30 and 50), the test presents good performance, provided that, the number of variables does not exceed to 12; and, the formula chosen, whether for small samples. Under contaminated multivariate normal distribution, the LRT for independence between two groups of variables have high values of power, but is not robust, because it has high rates of type I error in any scenario evaluated. / O teste de razão de verossimilhança para a independência entre dois grupos de variáveis permite identificar se há ou não relação de dependência entre dois grupos de variáveis, ou seja, se as covariâncias entre os dois grupos são nulas. Esse teste pressupõe normalidade multivariada dos dados, o que limita sua aplicação, em muitos estudos da área agronômica, em que se necessita utilizar, por exemplo, a análise de correlação canônica. O objetivo deste trabalho é avaliar o erro tipo I e o poder do teste de razão de verossimilhança (TRV) para independência entre dois grupos de variáveis em diversos cenários, constituídos pelas combinações de: 16 tamanhos de amostra; 40 combinações de número de variáveis dos dois grupos; e, nove graus de correlação entre as variáveis (para o poder); sob distribuição normal multivariada e distribuição normal multivariada contaminada, bem como, comparar, nos diferentes cenários, duas fórmulas para cálculo da estatística do teste. Dessa forma, foram avaliados o efeito de 640 e 5760 cenários sobre as taxas de erro tipo I e poder, respectivamente, em cada uma das distribuições de probabilidade e fórmulas. A avaliação do desempenho do TRV foi realizada por meio de simulação computacional pelo método Monte Carlo, utilizando-se 2000 simulações em cada um dos cenários gerados. Em situação de normalidade multivariada: quando o número de variáveis é grande (p= 24), o TRV para a independência entre dois grupos de variáveis, controla as taxas de erro tipo I e apresentou poder elevado, em tamanhos de amostra superiores a 100 e 500, com uso das fórmulas para pequenas e grandes amostras, respectivamente; e, para tamanhos amostrais pequenos (n= 25, 30 e 50), o teste apresenta bom desempenho, desde que, o número de variáveis não exceda a 12; e, a fórmula escolhida, seja para pequenas amostras. Sob distribuição normal multivariada contaminada, o TRV para a independência entre dois grupos de variáveis possui elevados valores de poder, mas não é robusto, pois apresenta elevadas taxas de erro tipo I, em qualquer cenário avaliado.

The concept of outlier detection by statistical hypothesis testing in geodesy is briefly reviewed. The performance of such tests can only be measured or optimized with respect to a proper alternative hypothesis. Firstly, we discuss the important question whether gross errors should be treated as non-random quantities or as random variables. In the first case, the alternative hypothesis must be based on the common mean shift model, while in the second case, the variance inflation model is appropriate. Secondly, we review possible formulations of alternative hypotheses (inherent, deterministic, slippage, mixture) and discuss their implications. As measures of optimality of an outlier detection, we propose the premium and protection, which are briefly reviewed. Finally, we work out a practical example: the fit of a straight line. It demonstrates the impact of the choice of an alternative hypothesis for outlier detection. / Das Konzept der Ausreißererkennung durch statistische Hypothesentests in der Geodäsie wird kurz überblickt. Die Leistungsfähigkeit solch eines Tests kann nur gemessen oder optimiert werden in Bezug auf eine geeignete Alternativhypothese. Als erstes diskutieren wir die wichtige Frage, ob grobe Fehler als nicht-zufällige oder zufällige Größen behandelt werden sollten. Im ersten Fall muss die Alternativhypothese auf das Mean-Shift-Modell gegründet werden, im zweiten Fall ist das Variance-Inflation-Modell passend. Als zweites stellen wir mögliche Formulierungen von Alternativhypothesen zusammen und diskutieren ihre Implikationen. Als Optimalitätsmaß schlagen wir das Premium-Protection-Maß vor, welches kurz überblickt wird. Schließlich arbeiten wir ein praktisches Beispiel aus: Die Anpassung einer ausgleichenden Gerade. Es zeigt die Auswirkung der Wahl einer Alternativhypothese für die Ausreißererkennung.

The concept of outlier detection by statistical hypothesis testing in geodesy is briefly reviewed. The performance of such tests can only be measured or optimized with respect to a proper alternative hypothesis. Firstly, we discuss the important question whether gross errors should be treated as non-random quantities or as random variables. In the first case, the alternative hypothesis must be based on the common mean shift model, while in the second case, the variance inflation model is appropriate. Secondly, we review possible formulations of alternative hypotheses (inherent, deterministic, slippage, mixture) and discuss their implications. As measures of optimality of an outlier detection, we propose the premium and protection, which are briefly reviewed. Finally, we work out a practical example: the fit of a straight line. It demonstrates the impact of the choice of an alternative hypothesis for outlier detection. / Das Konzept der Ausreißererkennung durch statistische Hypothesentests in der Geodäsie wird kurz überblickt. Die Leistungsfähigkeit solch eines Tests kann nur gemessen oder optimiert werden in Bezug auf eine geeignete Alternativhypothese. Als erstes diskutieren wir die wichtige Frage, ob grobe Fehler als nicht-zufällige oder zufällige Größen behandelt werden sollten. Im ersten Fall muss die Alternativhypothese auf das Mean-Shift-Modell gegründet werden, im zweiten Fall ist das Variance-Inflation-Modell passend. Als zweites stellen wir mögliche Formulierungen von Alternativhypothesen zusammen und diskutieren ihre Implikationen. Als Optimalitätsmaß schlagen wir das Premium-Protection-Maß vor, welches kurz überblickt wird. Schließlich arbeiten wir ein praktisches Beispiel aus: Die Anpassung einer ausgleichenden Gerade. Es zeigt die Auswirkung der Wahl einer Alternativhypothese für die Ausreißererkennung.