最近三十年來,最佳經濟設計管制圖已被考慮用來維持製程的穩定.由於在 實務上■管制圖被廣泛使用,是以大多數管制圖經濟模型的發展,都以單一 非機遇因素下的■管制圖為研究對象,但在實務上製程常會受二個或二個 以上非機遇因素的干擾.是以本研究利用更新理論方法建立二個非機遇因 素成本模式.又為使成本模式包含顧客的聲音以顯示品質的重要,本研究提 出以產品出廠後對社會的損失替代傳統上的成本考量.當推導出能反應顧 客滿意度的二個非機遇因素製程成本模式後,藉著最佳化技巧可決定■管 制圖的最佳設計參數值,並由例子的分析說明模式參數對最佳設計參數值 的影響 .另外,■經濟管制圖與Shewhart■管制圖間的成本比較顯現前者 能有顯著改善.最後,在考慮損失函數下■管制圖的建立與應用將被舉例說 明.

Dynamic Linear Models are a state space model framework based on the Kalman filter. We use this framework to do seasonal adjustments of empirical and artificial data. A simple model and an extended model based on Gibbs sampling are used and the results are compared with the results of a standard seasonal adjustment method. The state space approach is then extended to discuss direct and indirect seasonal adjustments. This is achieved by applying a seasonal level model with no trend and some specific input variances that render different signal-to-noise ratios. This is illustrated for a system consisting of two artificial time series. Relative efficiencies between direct, indirect and multivariate, i.e. optimal, variances are then analyzed. In practice, standard seasonal adjustment packages do not support optimal/multivariate seasonal adjustments, so a univariate approach to simultaneous estimation is presented by specifying a Holt-Winters exponential smoothing method. This is applied to two sets of time series systems by defining a total loss function that is specified with a trade-off weight between the individual series’ loss functions and their aggregate loss function. The loss function is based on either the more conventional squared errors loss or on a robust Huber loss. The exponential decay parameters are then estimated by minimizing the total loss function for different trade-off weights. It is then concluded what approach, direct or indirect seasonal adjustment, is to be preferred for the two time series systems. The dynamic linear modeling approach is also applied to Swedish political opinion polls to assert the true underlying political opinion when there are several polls, with potential design effects and bias, observed at non-equidistant time points. A Wiener process model is used to model the change in the proportion of voters supporting either a specific party or a party block. Similar to stock market models, all available (political) information is assumed to be capitalized in the poll results and is incorporated in the model by assimilating opinion poll results with the model through Bayesian updating of the posterior distribution. Based on the results, we are able to assess the true underlying voter proportion and additionally predict the elections. / <p>At the time of doctoral defence the following papers were unpublished and had a status as follows: Paper 3: Manuscript; Paper 4: Manuscripts</p>

This thesis deals with random-size subset selection and ranking procedures• • • )|(derived through likelihood ratios, mainly in terms of the P -approach.Let IT , . .. , IT, be k(&gt; 2) populations such that IR.(i = l, . . . , k) hasJ_ K. — 12the normal distribution with unknwon mean 0. and variance a.a , where a.i i i2 . . is known and a may be unknown; and that a random sample of size n^ istaken from . To begin with, we give procedure (with tables) whichselects IT. if sup L(0;x) &gt;c SUD L(0;X), where SÎ is the parameter space1for 0 = (0-^, 0^) ; where (with c: ß) is the set of all 0 with0. = max 0.; where L(*;x) is the likelihood function based on the total1sample; and where c is the largest constant that makes the rule satisfy theP*-condition. Then, we consider other likelihood ratios, with intuitivelyreasonable subspaces of ß, and derive several new rules. Comparisons amongsome of these rules and rule R of Gupta (1956, 1965) are made using differentcriteria; numerical for k=3, and a Monte-Carlo study for k=10.For the case when the populations have the uniform (0,0^) distributions,and we have unequal sample sizes, we consider selection for the populationwith min 0.. Comparisons with Barr and Rizvi (1966) are made. Generalizai&lt;j&lt;k Jtions are given.Rule R^ is generalized to densities satisfying some reasonable assumptions(mainly unimodality of the likelihood, and monotonicity of the likelihoodratio). An exponential class is considered, and the results are exemplifiedby the gamma density and the Laplace density. Extensions and generalizationsto cover the selection of the t best populations (using various requirements)are given. Finally, a discussion oil the complete ranking problem,and on the relation between subset selection based on likelihood ratios andstatistical inference under order restrictions, is given. / digitalisering@umu

The objective of this study is to compare Bayesian and parametric approaches to determine the best for estimating reliability in complex systems. Determining reliability is particularly important in business and medical contexts. As expected, the Bayesian method showed the best results in assessing the reliability of systems. In the first study, the Bayesian reliability function under the Higgins-Tsokos loss function using Jeffreys as its prior performs similarly as when the Bayesian reliability function is based on the squared-error loss. In addition, the Higgins-Tsokos loss function was found to be as robust as the squared-error loss function and slightly more efficient. In the second study, we illustrated that--through the power law intensity function--Bayesian analysis is applicable in the power law process. The power law intensity function is the key entity of the power law process (also called the Weibull process or the non-homogeneous Poisson process). It gives the rate of change of a system's reliability as a function of time. First, using real data, we demonstrated that one of our two parameters behaves as a random variable. With the generated estimates, we obtained a probability density function that characterizes the behavior of this random variable. Using this information, under the commonly used squared-error loss function and with a proposed adjusted estimate for the second parameter, we obtained a Bayesian reliability estimate of the failure probability distribution that is characterized by the power law process. Then, using a Monte Carlo simulation, we showed the superiority of the Bayesian estimate compared with the maximum likelihood estimate and also the better performance of the proposed estimate compared with its maximum likelihood counterpart. In the next study, a Bayesian sensitivity analysis was performed via Monte Carlo simulation, using the same parameter as in the previous study and under the commonly used squared-error loss function, using mean square error comparison. The analysis was extended to the second parameter as a function of the first, based on the relationship between their maximum likelihood estimates. The simulation procedure demonstrated that the Bayesian estimates are superior to the maximum likelihood estimates and that the selection of the prior distribution was sensitive. Secondly, we found that the proposed adjusted estimate for the second parameter has better performance under a noninformative prior. In the fourth study, a Bayesian approach was applied to real data from breast cancer research. The purpose of the study was to investigate the applicability of a Bayesian analysis to survival time of breast cancer data and to justify the applicability of the Bayesian approach to this domain. The estimation of one parameter, the survival function, and hazard function were analyzed. The simulation analysis showed that the Bayesian estimate of the parameter performed better compared with the estimated value under the Wheeler procedure. The excellent performance of the Bayesian estimate is reflected even for small sample sizes. The Bayesian survival function was also found to be more efficient than its parametric counterpart. In the last study, a Bayesian analysis was carried out to investigate the sensitivity to the choice of the loss function. One of the parameters of the distribution that characterized the survival times for breast cancer data was estimated applying a Bayesian approach and under two different loss functions. Also, the estimates of the survival function were determined under the same setting. The simulation analysis showed that the choice of the squared-error loss function is robust in estimating the parameter and the survival function.

Uma das principais preocupações da macroeconomia é a compreensão da dinâmica da inflação no curto prazo. Entender como a inflação se relaciona com a atividade econômica é decisivo para traçar estratégias de desinflação, assim como, de determinação da trajetória de política monetária. Uma questão que surge é qual a forma exata da relação inflação-produto. Ou seja, podemos caracterizar essa relação como não linear? Se sim, qual a forma dessa não linearidade? Para responder a essas perguntas, estimou-se a relação inflação-produto de forma não-paramétrica através de um local linear kernel estimator. O resultado da estimação gerou uma forma funcional a qual foi aproximada pela estimação, via GMM, de uma curva de Phillips Novo-Keynesiana Híbrida. Essa abordagem foi aplicada para o Brasil a partir de 2000. As estimações sugeriram que a dinâmica da inflação brasileira é melhor descrita quando adiciona-se um termo cúbico relativo ao hiato do produto, ou seja, a inflação brasileira mostrou-se state-dependent. / One of the most important macroeconomics’ concerns is the comprehension about sort-run inflation dynamic. To understand how inflation relates to economic activity is crucial to decision-making in disinflation strategies, as well as in monetary policy paths. A question that arises is what does real form of relation inflation-output trade-off? Could one characterize it as a non-linear relation? If does, what is the shape of this non-linear relation? To answer those questions, we estimate the inflation-output relation non-parametrically using a local linear kernel estimator. The functional form achieved was approximated by a New-Keynesian Hybrid Phillips Curve, which one was estimated by GMM. This approach was applied to Brazil since 2000. We have found evidence that Brazilian inflation dynamic is better described adding a cubic term related to output gap, in other words, the Brazilian inflation is state-dependent.

Uma das principais preocupações da macroeconomia é a compreensão da dinâmica da inflação no curto prazo. Entender como a inflação se relaciona com a atividade econômica é decisivo para traçar estratégias de desinflação, assim como, de determinação da trajetória de política monetária. Uma questão que surge é qual a forma exata da relação inflação-produto. Ou seja, podemos caracterizar essa relação como não linear? Se sim, qual a forma dessa não linearidade? Para responder a essas perguntas, estimou-se a relação inflação-produto de forma não-paramétrica através de um local linear kernel estimator. O resultado da estimação gerou uma forma funcional a qual foi aproximada pela estimação, via GMM, de uma curva de Phillips Novo-Keynesiana Híbrida. Essa abordagem foi aplicada para o Brasil a partir de 2000. As estimações sugeriram que a dinâmica da inflação brasileira é melhor descrita quando adiciona-se um termo cúbico relativo ao hiato do produto, ou seja, a inflação brasileira mostrou-se state-dependent. / One of the most important macroeconomics’ concerns is the comprehension about sort-run inflation dynamic. To understand how inflation relates to economic activity is crucial to decision-making in disinflation strategies, as well as in monetary policy paths. A question that arises is what does real form of relation inflation-output trade-off? Could one characterize it as a non-linear relation? If does, what is the shape of this non-linear relation? To answer those questions, we estimate the inflation-output relation non-parametrically using a local linear kernel estimator. The functional form achieved was approximated by a New-Keynesian Hybrid Phillips Curve, which one was estimated by GMM. This approach was applied to Brazil since 2000. We have found evidence that Brazilian inflation dynamic is better described adding a cubic term related to output gap, in other words, the Brazilian inflation is state-dependent.

Esta dissertação apresenta um estudo desenvolvido com o intuito de consolidar uma metodologia para a otimização de projeto de porta-sedes de uma válvula de esfera trunnion. Este trabalho está dividido em dois artigos. Primeiramente, é apresentado um estudo comparativo entre diferentes modelos de porta-sedes, realizado com o apoio do método dos elementos finitos (FEA). O porta-sede de melhor desempenho foi determinado utilizando a Função de Perda Quadrática Multivariada. O objetivo principal deste primeiro artigo é identificar os principais parâmetros da geometria de um porta-sede, que possam garantir o desempenho funcional da válvula e correspondente atendimento dos requisitos de qualidade. O segundo artigo descreve uma aplicação da metodologia de Projeto de Experimentos (DOE), conduzida com o intuito de identificar a configuração geométrica da válvula que conduza a condição ótima de funcionamento, fornecendo, desta forma, subsídio para a área de Desenvolvimento de Produtos na elaboração de válvulas mais robustas. Uma das principais contribuições deste trabalho é a constatação que os quatro fatores controláveis incluídos no estudo exercem efeito significativos sobre as variáveis de resposta utilizadas (pressão de contato e força de reação). Excetuando-se o fator “pressão de operação da válvula”, que caracteriza a condição operação, mas não é um parâmetro de projeto, o fator que revelou efeito mais pronunciado sobre as variáveis resposta foi a “área da pista de vedação”. / This thesis presents a study conducted in order to consolidate a methodology for seat-retainer design optimization of a trunnion ball valve. This work is divided in two papers. Initially a comparative study between different seat-retainer models, developed with the support of the finite element analysis (FEA), is presented. The best performance seat-retainer was determined using the Multivariate Quadratic Loss Function. The main purpose of this first article is to identify the main parameters of the seat-retainer geometry, which could ensure the functional performance of the valve and corresponding quality requirements. The second paper describes an application of Design of Experiments (DOE) methodology, conducted in order to identify the geometric configuration of the valve that leads to the optimal operating condition, providing thereby, contribution to the Product Development area in designing more robust valves. The main contribution of this work is the finding that the four control factors included in the study exert significant effect on the response variables used (contact pressure and reaction force). Except for the factor "valve operating pressure" that characterizes the operation condition, but is not a design parameter, the factor that showed more pronounced effect on the response variables was the “seat sealing area”.

Uma das principais preocupações da macroeconomia é a compreensão da dinâmica da inflação no curto prazo. Entender como a inflação se relaciona com a atividade econômica é decisivo para traçar estratégias de desinflação, assim como, de determinação da trajetória de política monetária. Uma questão que surge é qual a forma exata da relação inflação-produto. Ou seja, podemos caracterizar essa relação como não linear? Se sim, qual a forma dessa não linearidade? Para responder a essas perguntas, estimou-se a relação inflação-produto de forma não-paramétrica através de um local linear kernel estimator. O resultado da estimação gerou uma forma funcional a qual foi aproximada pela estimação, via GMM, de uma curva de Phillips Novo-Keynesiana Híbrida. Essa abordagem foi aplicada para o Brasil a partir de 2000. As estimações sugeriram que a dinâmica da inflação brasileira é melhor descrita quando adiciona-se um termo cúbico relativo ao hiato do produto, ou seja, a inflação brasileira mostrou-se state-dependent. / One of the most important macroeconomics’ concerns is the comprehension about sort-run inflation dynamic. To understand how inflation relates to economic activity is crucial to decision-making in disinflation strategies, as well as in monetary policy paths. A question that arises is what does real form of relation inflation-output trade-off? Could one characterize it as a non-linear relation? If does, what is the shape of this non-linear relation? To answer those questions, we estimate the inflation-output relation non-parametrically using a local linear kernel estimator. The functional form achieved was approximated by a New-Keynesian Hybrid Phillips Curve, which one was estimated by GMM. This approach was applied to Brazil since 2000. We have found evidence that Brazilian inflation dynamic is better described adding a cubic term related to output gap, in other words, the Brazilian inflation is state-dependent.

Esta dissertação apresenta um estudo desenvolvido com o intuito de consolidar uma metodologia para a otimização de projeto de porta-sedes de uma válvula de esfera trunnion. Este trabalho está dividido em dois artigos. Primeiramente, é apresentado um estudo comparativo entre diferentes modelos de porta-sedes, realizado com o apoio do método dos elementos finitos (FEA). O porta-sede de melhor desempenho foi determinado utilizando a Função de Perda Quadrática Multivariada. O objetivo principal deste primeiro artigo é identificar os principais parâmetros da geometria de um porta-sede, que possam garantir o desempenho funcional da válvula e correspondente atendimento dos requisitos de qualidade. O segundo artigo descreve uma aplicação da metodologia de Projeto de Experimentos (DOE), conduzida com o intuito de identificar a configuração geométrica da válvula que conduza a condição ótima de funcionamento, fornecendo, desta forma, subsídio para a área de Desenvolvimento de Produtos na elaboração de válvulas mais robustas. Uma das principais contribuições deste trabalho é a constatação que os quatro fatores controláveis incluídos no estudo exercem efeito significativos sobre as variáveis de resposta utilizadas (pressão de contato e força de reação). Excetuando-se o fator “pressão de operação da válvula”, que caracteriza a condição operação, mas não é um parâmetro de projeto, o fator que revelou efeito mais pronunciado sobre as variáveis resposta foi a “área da pista de vedação”. / This thesis presents a study conducted in order to consolidate a methodology for seat-retainer design optimization of a trunnion ball valve. This work is divided in two papers. Initially a comparative study between different seat-retainer models, developed with the support of the finite element analysis (FEA), is presented. The best performance seat-retainer was determined using the Multivariate Quadratic Loss Function. The main purpose of this first article is to identify the main parameters of the seat-retainer geometry, which could ensure the functional performance of the valve and corresponding quality requirements. The second paper describes an application of Design of Experiments (DOE) methodology, conducted in order to identify the geometric configuration of the valve that leads to the optimal operating condition, providing thereby, contribution to the Product Development area in designing more robust valves. The main contribution of this work is the finding that the four control factors included in the study exert significant effect on the response variables used (contact pressure and reaction force). Except for the factor "valve operating pressure" that characterizes the operation condition, but is not a design parameter, the factor that showed more pronounced effect on the response variables was the “seat sealing area”.

In this study a structural model of the South African stock market, the Johannesburg Stock Exchange (JSE), was developed and estimated econometrically. The study has made three important contributions to the literature. Firstly, a structural model of the South African stock market has been developed, which quantifies the relationships between the stock market and macroeconomic variables while analyzing the impact of foreign markets and phenomena such as contagion, policy changes and structural economic changes on the JSE. This will improve the economic agents’ understanding of the functioning of the stock market and potentially assist in forecasting the stock market. Secondly, investors are generally assumed to be risk and/or loss averse. This study explains how this risk and/or loss aversion of investors can cause asymmetry in stock prices and the study evaluates different types of stock market asymmetry with advanced econometric techniques such as the threshold cointegration test of Siklos and Enders (2001) and a Markov switching regime model. The Markov switching regime model is used to model the South African business cycle and to construct an indicator for the state of the business cycle, which is in turn used to introduce cyclical asymmetry in the stock market model. The Markov switching regime model is in itself a substantial contribution to the literature since no Markov switching regime model has been estimated for the South African business cycle yet. Apart from being used to capture cyclical asymmetry in the stock market, the Markov switching regime business cycle model can also be used to identify turning points in the South African economy and to model economic growth. Finally, the forecasting performance of the stock market model developed in this study is compared to other stock market models. According to the results, this model is preferred to the other stock market models in terms of modelling and forecasting the level and direction of the JSE. This means that investors and policy markets can use this model to simulate the impact of changes in macroeconomic indicators on the future course of the stock market and use it to develop profitable trading rules. / Thesis (PhD (Econometrics))--University of Pretoria, 2005. / Economics / unrestricted