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Three-level designs robust to model uncertaintyTsai, Pi-Wen January 1998 (has links)
No description available.
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Heteroscedasticity in financial time seriesRuiz Ortega, Esther January 1992 (has links)
This thesis deals with two different topics, both related to modelling time-varying variances in high frequency financial time series. The first topic concerns the estimation of unobserved component models with autoregressive conditional heteroscedastic (ARCH) effects. The second topic concerns the quasi-maximum likelihood estimation of stochastic variance processes. These are an alternative to ARCH processes for modelling conditionally heteroscedastic time series. The motivation of the work is based on the increasing interest in the financial area in modelling volatility. In financial markets, many decisions are based on the volatility of a specific stock or index, which is closely related to the variance. Therefore, it is important to develop good statistical models able to describe time-varying variances. 2
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A Family of Symmetric Distributions and Best Linear Unbiased Estimators of its ParametersKumra, Sushil 11 1900 (has links)
<p> A family of symmetric distributions is introduced. The means, variances and covariances of ordered observations from the family are calculated. The best linear unbiased estimators of the mean and standard deviation are constructed for complete and censored samples. A computer technique is developed to evaluate range-dependent double integrals. </p> / Thesis / Master of Science (MSc)
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Techniques to handle missing values in a factor analysisTurville, Christopher, University of Western Sydney, Faculty of Informatics, Science and Technology January 2000 (has links)
A factor analysis typically involves a large collection of data, and it is common for some of the data to be unrecorded. This study investigates the ability of several techniques to handle missing values in a factor analysis, including complete cases only, all available cases, imputing means, an iterative component method, singular value decomposition and the EM algorithm. A data set that is representative of that used for a factor analysis is simulated. Some of this data are then randomly removed to represent missing values, and the performance of the techniques are investigated over a wide range of conditions. Several criteria are used to investigate the abilities of the techniques to handle missing values in a factor analysis. Overall, there is no one technique that performs best for all of the conditions studied. The EM algorithm is generally the most effective technique except when there are ill-conditioned matrices present or when computing time is of concern. Some theoretical concerns are introduced regarding the effects that changes in the correlation matrix will have on the loadings of a factor analysis. A complicated expression is derived that shows that the change in factor loadings as a result of change in the elements of a correlation matrix involves components of eigenvectors and eigenvalues. / Doctor of Philosophy (PhD)
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Modélisation et contrôle statistique de l'analyse cytométrique de la ploi͏̈die en cancérologieGuillaud, Martial 07 May 1993 (has links) (PDF)
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Combination of Levene-Type Tests and a Finite-Intersection Method for Testing Trends in VariancesNoguchi, Kimihiro January 2009 (has links)
The problem of detecting monotonic increasing/decreasing trends in variances from k samples is widely met in many applications, e.g. financial data analysis, medical and environmental studies. However, most of the tests for equality of variances against ordered alternatives rely on the assumption of normality. Such tests are often non-robust to departures from normality, which eventually leads to unreliable conclusions. In this thesis, we propose a combination of a robust Levene-type test and a finite-intersection method, which relaxes the assumption of normality. The new combined procedure yields a more accurate estimate of sizes of the test and provides competitive powers. In addition, we discuss various modifications of the proposed test for unbalanced design cases. We present theoretical justifications of the new test and illustrate its applications by simulations and case studies.
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Combination of Levene-Type Tests and a Finite-Intersection Method for Testing Trends in VariancesNoguchi, Kimihiro January 2009 (has links)
The problem of detecting monotonic increasing/decreasing trends in variances from k samples is widely met in many applications, e.g. financial data analysis, medical and environmental studies. However, most of the tests for equality of variances against ordered alternatives rely on the assumption of normality. Such tests are often non-robust to departures from normality, which eventually leads to unreliable conclusions. In this thesis, we propose a combination of a robust Levene-type test and a finite-intersection method, which relaxes the assumption of normality. The new combined procedure yields a more accurate estimate of sizes of the test and provides competitive powers. In addition, we discuss various modifications of the proposed test for unbalanced design cases. We present theoretical justifications of the new test and illustrate its applications by simulations and case studies.
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A test for curvature in 2^k designs with center points and analysis for proportional data in response surface modelsTsai, Pei-wen 26 August 2009 (has links)
The response surface methodology is a useful method to find the optimum response in an experiment. In this work, a new test statistic with only few replicates at the center point for curvature detection is discussed. The performance of the new
statistic is investigated through simulation. In the second part of this work, when
the response variable is of the proportional type taking only values between 0 and 1,
some analysis methods are compared based on the predicted variances on the design
region.
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Variação genética e adaptabilidade evolutiva de Rhizoctonia solani AG-1 da soja sob condições de estresseFerro, Camila Geovana [UNESP] 01 February 2012 (has links) (PDF)
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ferro_cg_me_jabo.pdf: 390303 bytes, checksum: 9d8f1206031713ae8ef90f14317d0c17 (MD5) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Estresse devido a mudanças ambientais pode impactar caracteres quantitativos através de alterações nas variâncias, genética e ambiental. Populações do patógeno da mela da soja, Rhizoctonia solani grupo de anastomose AG-1 IA, são altamente diferenciadas geneticamente ao longo de um gradiente latitudinal nas mais importantes regiões de cultivo de soja do Brasil. Entretanto, os processos evolutivos que guiaram a adaptação regional dessas populações são ainda desconhecidos. Neste trabalho foi testada a hipótese de que o estresse de temperatura elevada pode aumentar a variação genética para caracteres quantitativos, como a resistência a fungicida de amplo espectro, no fungo R. solani AG-1 IA da soja. Isto é o mesmo que testar se um aumento da temperatura, além da temperatura ótima para crescimento, resulta em aumento da herdabilidade de senso amplo para tolerância a um fungicida. Objetivou-se, especificamente, testar o efeito do estresse de temperatura sobre a variação genética para tolerância ao fungicida oxicloreto de cobre e avaliar a importância relativa da variação genética neutra e da seleção natural sobre a divergência e adaptação regional de populações de R. solani AG-1 IA da soja. Para tanto, avaliou-se o crescimento micelial in vitro de três populações brasileiras de R. solani AG-1 IA da soja sob dois regimes de temperatura, ótimo (25°C) e acima do ótimo (33,5°C), e sob três concentrações de oxicloreto de cobre: nenhum fungicida, 0,42 e 0,84 g.L-1. Foram determinadas os componentes de evolutibilidade: variância genética (IG), ambiental (IE) e a herdabilidade no sentido amplo (h2) para o crescimento micelial nas diferentes condições. Comparou-se, também, a diferenciação fenotípica por caracteres quantitativos (QST) e a diferenciação genética neutra (baseada em dados... / Stress due to environmental changes can impact quantitative traits through changes in variances, genetic and environmental. Populations of soybean foliar blight pathogen, Rhizoctonia solani anastomosis group AG-1 IA, are highly genetically differentiated along a latitudinal gradient in the most important Brazilian cropping areas. However, the evolutionary processes that have guided the regional adaptation of these populations are still unknown. In this study we tested the hypothesis that high temperature stress can increase the genetic variation for quantitative traits such as the tolerance to a broadspectrum fungicide, in the fungus R. solani AG-1 IA from soybean. This is the same as testing whether a temperature increase, beyond the optimum temperature for growth, results in increased broad sense heritability for fungicide tolerance. The specific objective was to test the effects of temperature stress on the genetic variation for tolerance to cupper oxychloride and to assess the relative importance of neutral genetic variation and natural selection on the divergence and local adaptation of R. solani AG-1 IA populations from soybean. We evaluated the in vitro mycelial growth of three Brazilian populations of R. solani AG-1 IA from soybean under two temperature regimes, optimal (25°C) and above optimal (33.5°C), and under three concentrations of cupper oxychloride: no fungicide, 0.42 and 0.84 g.L-1. We determined the components of evolvability: genetic (IG) and environmental (IE) variances and the broad-sense heritability (h2) for mycelial growth under these conditions. We also compared the phenotypic differentiation for quantitative traits (QST) and neutral genetic differentiation (based on microsatellite data) between three pairs of populations (FST). As measures of fungal phenotypic responses... (Complete abstract click electronic access below)
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Variação genética e adaptabilidade evolutiva de Rhizoctonia solani AG-1 da soja sob condições de estresse /Ferro, Camila Geovana. January 2012 (has links)
Orientador: Paulo Cezar Ceresini / Banca: Margarete Camargo / Banca: Jaqueline Rosemeire Verzignassi / Resumo: Estresse devido a mudanças ambientais pode impactar caracteres quantitativos através de alterações nas variâncias, genética e ambiental. Populações do patógeno da mela da soja, Rhizoctonia solani grupo de anastomose AG-1 IA, são altamente diferenciadas geneticamente ao longo de um gradiente latitudinal nas mais importantes regiões de cultivo de soja do Brasil. Entretanto, os processos evolutivos que guiaram a adaptação regional dessas populações são ainda desconhecidos. Neste trabalho foi testada a hipótese de que o estresse de temperatura elevada pode aumentar a variação genética para caracteres quantitativos, como a resistência a fungicida de amplo espectro, no fungo R. solani AG-1 IA da soja. Isto é o mesmo que testar se um aumento da temperatura, além da temperatura ótima para crescimento, resulta em aumento da herdabilidade de senso amplo para tolerância a um fungicida. Objetivou-se, especificamente, testar o efeito do estresse de temperatura sobre a variação genética para tolerância ao fungicida oxicloreto de cobre e avaliar a importância relativa da variação genética neutra e da seleção natural sobre a divergência e adaptação regional de populações de R. solani AG-1 IA da soja. Para tanto, avaliou-se o crescimento micelial in vitro de três populações brasileiras de R. solani AG-1 IA da soja sob dois regimes de temperatura, ótimo (25°C) e acima do ótimo (33,5°C), e sob três concentrações de oxicloreto de cobre: nenhum fungicida, 0,42 e 0,84 g.L-1. Foram determinadas os componentes de evolutibilidade: variância genética (IG), ambiental (IE) e a herdabilidade no sentido amplo (h2) para o crescimento micelial nas diferentes condições. Comparou-se, também, a diferenciação fenotípica por caracteres quantitativos (QST) e a diferenciação genética neutra (baseada em dados... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Stress due to environmental changes can impact quantitative traits through changes in variances, genetic and environmental. Populations of soybean foliar blight pathogen, Rhizoctonia solani anastomosis group AG-1 IA, are highly genetically differentiated along a latitudinal gradient in the most important Brazilian cropping areas. However, the evolutionary processes that have guided the regional adaptation of these populations are still unknown. In this study we tested the hypothesis that high temperature stress can increase the genetic variation for quantitative traits such as the tolerance to a broadspectrum fungicide, in the fungus R. solani AG-1 IA from soybean. This is the same as testing whether a temperature increase, beyond the optimum temperature for growth, results in increased broad sense heritability for fungicide tolerance. The specific objective was to test the effects of temperature stress on the genetic variation for tolerance to cupper oxychloride and to assess the relative importance of neutral genetic variation and natural selection on the divergence and local adaptation of R. solani AG-1 IA populations from soybean. We evaluated the in vitro mycelial growth of three Brazilian populations of R. solani AG-1 IA from soybean under two temperature regimes, optimal (25°C) and above optimal (33.5°C), and under three concentrations of cupper oxychloride: no fungicide, 0.42 and 0.84 g.L-1. We determined the components of evolvability: genetic (IG) and environmental (IE) variances and the broad-sense heritability (h2) for mycelial growth under these conditions. We also compared the phenotypic differentiation for quantitative traits (QST) and neutral genetic differentiation (based on microsatellite data) between three pairs of populations (FST). As measures of fungal phenotypic responses... (Complete abstract click electronic access below) / Mestre
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