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Stewart, Laura M. "Correlated observation errors in data assimilation." Thesis, University of Reading, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.553080.
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Data assimilation techniques combine observations and prior model forecasts to create initial conditions for numerical weather prediction (NWP). The relative weighting as- signed to each observation in the analysis is determined by the error associated with its measurement. Remote sensing data often have correlated errors, but the correlations are typically ignored in NWP. As operational centres move towards high-resolution fore- casting, the assumption of uncorrelated errors becomes impractical. This thesis provides new evidence that including observation error correlations in data assimilation schemes is both feasible and beneficial. We study the dual problem of quantifying and modelling observation error correlation structure. Firstly, in original work using statistics from the Met Office 4D- Var assimilation system, we diagnose strong cross-channel error eo- variances for the IASI satellite instrument. We then see how in a 3D- Var framework, information content is degraded under the assumption of uncorrelated errors, while re- tention of an approximate correlation gives clear benefits. These novel results motivate further study. We conclude by modelling observation error correlation structure in the framework of a one-dimensional shallow water model. Using an incremental 4D- Var assimilation system we observe that analysis errors are smallest when correlated error covariance matrix approximations are used over diagonal approximations. The new re- sults reinforce earlier conclusions on the benefits of including some error correlation structure.
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Pazman, Andrej, and Werner Müller. "Optimal Design of Experiments Subject to Correlated Errors." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 2000. http://epub.wu.ac.at/64/1/document.pdf.
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In this paper we consider optimal design of experiments in the case of correlated observations, when no replications are possible. This situation is typical when observing a random process or random field with known covariance structure. We present a theorem which demonstrates that the computation of optimum exact designs corresponds to solving minimization problems in terms of design measures. (author's abstract)Series: Forschungsberichte / Institut für Statistik
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Fedorov, Valery V., and Werner Müller. "Optimum design for correlated processes via eigenfunction expansions." Institut für Statistik und Mathematik, WU Vienna University of Economics and Business, 2004. http://epub.wu.ac.at/622/1/document.pdf.
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In this paper we consider optimum design of experiments for correlated observations. We approximate the error component of the process by an eigenvector expansion of the corresponding covariance function. Furthermore we study the limit behavior of an additional white noise as a regularization tool. The approach is illustrated by some typical examples. (authors' abstract)Series: Research Report Series / Department of Statistics and Mathematics
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Adelaar, Glenn A. "An empirical investigation of nonlinear least squares estimation with correlated errors." Thesis, Georgia Institute of Technology, 1986. http://hdl.handle.net/1853/25586.
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Pazman, Andrej, and Werner Müller. "Extended Information Matrices for Optimal Designs when the Observations are Correlated." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 1996. http://epub.wu.ac.at/1416/1/document.pdf.
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Regression models with correlated errors lead to nonadditivity of the information matrix. This makes the usual approach of design optimization (approximation with a continuous design, application of an equivalence theorem, numerical calculations by a gradient algorithm) impossible. A method is presented that allows the construction of a gradient algorithm by altering the information matrices through adding of supplementary noise. A heuristic is formulated to circumvent the nonconvexity problem and the method is applied to typical examples from the literature. (author's abstract)Series: Forschungsberichte / Institut für Statistik
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Stehlik, Milan. "Further aspects on an example of D-optimal designs in the case of correlated errors." Institut für Statistik und Mathematik, WU Vienna University of Economics and Business, 2004. http://epub.wu.ac.at/670/1/document.pdf.
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The aim of this paper is discussion on particular aspects of the extension of a classic example in the design of experiments under the presence of correlated errors. Such extension allows us to study the effect of the correlation range on the design. We discuss the dependence of the information gained by the D-optimum design on the covariance bandwidth and also we concentrate to some technical aspects that occurs in such settings. (author's abstract)Series: Research Report Series / Department of Statistics and Mathematics
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Akdemir, Deniz. "Components Of Response Variance For Cluster Samples." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1206044/index.pdf.
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Measures of data quality are important for the evaluation and
improvement of survey design and procedures. A detailed investigation of the
sources, magnitude and impact of errors is necessary to identify how survey
design and procedures may be improved and how resources allocated more
efficiently among various aspects of the survey operation. A major part of this
thesis is devoted to the overview of statistical theory and methods for
measuring the contribution of response variability to the overall error of a
survey.
A very common practice in surveys is to select groups (clusters) of
elements together instead of independent selection of elements. In practice cluster samples tend to produce higher sampling variance for statistics than
element samples of the same size. Their frequent use stems from the desirable
cost features that they have.
Most data collection and sample designs involve some overlapping
between interviewer workload and the sampling units (clusters). For those
cases, a proportion of the measurement variance, which is due to interviewers,
is reflected to some degree in the sampling variance calculations.
The prime purpose in this thesis is to determine a variance formula that
decomposes the total variance into sampling and measurement variance
components for two commonly used data collection and sample designs. Once
such a decomposition is obtained, determining an optimum allocation in
existence of measurement errors would be possible.
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Savanhu, Richard. "Bayesian estimation of stochastic volatility models with fat tails and correlated errors applied to the South African financial market." Master's thesis, University of Cape Town, 2011. http://hdl.handle.net/11427/11085.
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Includes bibliographical references (leaves 39-40).In this study we apply Markov Chain Monte Carlo methods in the Bayesian framework to estimate Stochastic Volatility models using South African financial market data. A single move Gibbs sampler is used to sample parameters from the posterior distribution. Volatility is used as measure of an asset's risk. It is particularly important in risk management, derivatives pricing, and portfolio selection. When pricing derivatives it is important to quote the correct volatility trading in the market, hence there is need for good estimates of volatility. To capture the stylised facts about asset returns we used the model extended for fat tails and correlated errors. To support this model against the basic model of Taylor (1986), we computed Bayes Factors of Jacquier, Polson and Ross (2004). The extended model was found to be far superior to the basic model.
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Lohnes, Mitchell T. "Multivariate approaches to qualitative and quantitative analysis in chemistry, I. Calibration with correlated errors; II. Window target-testing factor analysis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ36495.pdf.
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Martins, Vera Lúcia Milani. "Comparação de combinação de previsões correlacionadas e não correlacionadas com as suas previsões individuais : um estudo com séries industriais." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2011. http://hdl.handle.net/10183/29051.
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A realização de previsões adequadas nas indústrias oportuniza o correto dimensionamento de diversos aspectos da gestão da produção. Um dos métodos empregados no intuito de melhorar a precisão das previsões é conhecido como combinação de previsões. Ao longo dos anos, foram publicados estudos de combinação a fim de comparar os métodos já existentes e indicar entre estes, qual o mais acurado. No entanto não há unanimidade em suas conclusões. Entre as combinações existentes, o método da média aritmética é reconhecido como um dos mais utilizados, enquanto que o método da variância mínima é por vezes apresentado como mais acurado e permite em sua formulação a consideração ou não da correlação entre os erros das previsões individuais. No intuito de identificar, para previsões em séries reais industriais, se existe diferença entre a acurácia das previsões individuais e de suas combinações é que este estudo está sendo proposto. A modelagem individual abordada é a ARIMA e a RNA e as medidas empregadas para a escolha do método mais preciso são MAPE, MAE e MSE. O trabalho está estruturado em três artigos, nos quais se realizam comparações entre técnicas de previsão individual e suas combinações. O Artigo 1 aborda a comparação entre as técnicas de previsão individual e as combinações por média aritmética e variância mínima simplificada. O Artigo 2, por sua vez, apresenta um estudo comparativo das técnicas de previsão individuais e as combinações por média aritmética e variância mínima, utilizando a correlação entre os erros na obtenção dos pesos de cada previsão. Por fim, um comparativo entre as três combinações que contemplam este estudo é explicitado no Artigo 3. Como principal resultado, destaca-se o desempenho superior obtido por meio dos métodos de combinação por variância mínima, em especial o método simplificado.The adequate forecasting in industries allows the correct sizing of many aspects of production management. A method used to improve the precision of forecasts is the combination of predictions. Over time, many studies were conducted to evaluate the existent methods and to indicate which one is the most precise. However, there is no unanimity in those studies conclusions. Among the combination methods, the arithmetic average is recognized as the broadly applied, while the minimum variance is sometimes presented as more accurate allowing to consider the correlation between the errors of individual forecasts or not. This study proposes to identify, in real industrial predictions series, if there are differences between accuracy of individual forecasts and their combinations. The individual predictions are performed by ARIMA and ANN models, and the measures used to choose the best method are MAPE, MAE and MSE. This dissertation is structured as three articles, in which a series of comparisons between individual prediction techniques and their combinations. Article 1 addresses the comparison between the individual prevision techniques and the combination methods of mean arithmetic and simplified minimum variance. Article 2 presents a comparative study between the individual prevision techniques and the combination methods of mean arithmetic and minimum variance, considering errors correlated. The comparison between the three combinations presented in the previous articles is explained in Article 3. As main result of the dissertation, it is highlighted the superior performance obtained with the minimum variance combined methods, specially the simplified method.
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Bayoh, Isaac M. "Accounting for Endogeneity and Spatially Correlated Errors in Hedonic Analyses with an Application to the Effects of Livestock Operations on Residential Property Values." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1275370128.
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Obage, Simone Cristina. "Uma análise bayesiana para dados composicionais." Universidade Federal de São Carlos, 2005. https://repositorio.ufscar.br/handle/ufscar/4505.
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Compositional data are given by vectors of positive numbers with sum equals to one. These kinds of data are common in many applications, as in geology, biology, economy among many others. In this paper, we introduce a Bayesian analysis for compositional data considering additive log-ratio (ALR) and Box-Cox transformations assuming a mul- tivariate normal distribution for correlated errors. These results generalize some existing Bayesian approaches assuming uncorrelated errors. We also consider the use of expo- nential power distributions for uncorrelated errors considering additive log-ratio (ALR) transformation. We illustrate the proposed methodology considering a real data set.
Dados Composicionais são dados por vetores com elementos positivos cuja soma é um. Exemplos típicos de dados desta natureza são encontrados nas mais diversas áreas; como em geologia, biologia, economia entre outras. Neste trabalho, introduzimos uma análise Bayesiana para dados composicionais considerando as transformações razão log-aditiva e Box-Cox, assumindo a distribuição normal multivariada para erros correlacionados. Estes resultados generalizam uma abordagem bayesiana assumindo erros não correlacionados. Também consideramos o uso da distribuição potência exponencial para erros não correla- cionados, assumindo a transformação razão log-aditiva. Nós ilustramos a metodologia proposta considerando um conjunto de dados reais.
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Kist, Airton 1971. "O uso de ondaletas em modelos FANOVA." [s.n.], 2011. http://repositorio.unicamp.br/jspui/handle/REPOSIP/307515.
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Orientador: Aluísio de Souza PinheiroTese (doutorado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica
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Resumo: O problema de estimação funcional vem sendo estudado de formas variadas na literatura. Uma possibilidade bastante promissora se dá pela utilização de bases ortonormais de wavelets (ondaletas). Essa solução _e interessante por sua: frugalidade; otimalidade assintótica; e velocidade computacional. O objetivo principal do trabalho é estender os testes do modelo FANOVA de efeitos fixos, com erros i.i.d., baseados em ondaletas propostos em Abramovich et al. (2004), para modelos FANOVA de efeitos fixos com erros dependentes. Propomos um procedimento iterativo tipo Cocharane-Orcutt para estimar os parâmetros e a função. A função é estimada de forma não paramétrica via estimador ondaleta que limiariza termo a termo ou estimador linear núcleo ondaleta. Mostramos que, com erros i.i.d., a convergência individual do estimador núcleo ondaleta em pontos diádicos para uma variável aleatória com distribuição normal implica na convergência conjunta deste vetor para uma variável aleatória com distribuição normal multivariada. Além disso, mostramos a convergência em erro quadrático do estimador nos pontos diádicos. Sob uma restrição é possível mostrar que este estimador converge nos pontos diádicos para uma variável com distribuição normal mesmo quando os erros são correlacionados. O vetor das convergências individuais também converge para uma variável normal multivariada
Abstract: The functional estimation problem has been studied variously in the literature. A promising possibility is by use of orthonormal bases of wavelets. This solution is appealing because of its: frugality, asymptotic optimality, and computational speed. The main objective of the work is to extend the tests of fixed effects FANOVA model with iid errors, based on wavelet proposed in Abramovich et al. (2004) to fixed effects FANOVA models with dependent errors. We propose an iterative procedure Cocharane-Orcutt type to estimate the parameters and function. The function is estimated through a nonparametric wavelet estimator that thresholded term by term or wavelet kernel linear estimator. We show that, with iid errors, the individual convergence of the wavelet kernel estimator in dyadic points for a random variable with normal distribution implies the joint convergence of this vector to a random variable with multivariate normal distribution. Furthermore, we show the convergence of the squared error estimator in the dyadic points. Under a restriction is possible to show that this estimator converges in dyadic points to a variable with normal distribution even when errors are correlated. The vector of individual convergences also converges to a multivariate normal variable
Doutorado
Estatistica
Doutor em Estatística
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Rosales, Marticorena Luis Francisco Verfasser], Tatyana [Akademischer Betreuer] [Gutachter] Krivobokova, Stephan von [Gutachter] Cramon-Taubadel, Thomas [Gutachter] [Kneib, Russell [Gutachter] Luke, Gerlind [Gutachter] Plonka-Hoch, and Dominic [Gutachter] Schuhmacher. "Empirical Bayesian Smoothing Splines for Signals with Correlated Errors: Methods and Applications / Luis Francisco Rosales Marticorena. Betreuer: Tatyana Krivobokova. Gutachter: Tatyana Krivobokova ; Stephan von Cramon-Taubadel ; Thomas Kneib ; Russell Luke ; Gerlind Plonka-Hoch ; Dominic Schuhmacher." Göttingen : Niedersächsische Staats- und Universitätsbibliothek Göttingen, 2016. http://d-nb.info/1111883467/34.
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Nimon, Kim. "Convergent Validity of Variables Residualized By a Single Covariate: the Role of Correlated Error in Populations and Samples." Thesis, University of North Texas, 2013. https://digital.library.unt.edu/ark:/67531/metadc271870/.
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This study examined the bias and precision of four residualized variable validity estimates (C0, C1, C2, C3) across a number of study conditions. Validity estimates that considered measurement error, correlations among error scores, and correlations between error scores and true scores (C3) performed the best, yielding no estimates that were practically significantly different than their respective population parameters, across study conditions. Validity estimates that considered measurement error and correlations among error scores (C2) did a good job in yielding unbiased, valid, and precise results. Only in a select number of study conditions were C2 estimates unable to be computed or produced results that had sufficient variance to affect interpretation of results. Validity estimates based on observed scores (C0) fared well in producing valid, precise, and unbiased results. Validity estimates based on observed scores that were only corrected for measurement error (C1) performed the worst. Not only did they not reliably produce estimates even when the level of modeled correlated error was low, C1 produced values higher than the theoretical limit of 1.0 across a number of study conditions. Estimates based on C1 also produced the greatest number of conditions that were practically significantly different than their population parameters.
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Kroeger, Lori A. "Neural Correlates of Error Detection in Math Facts." University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1353088326.
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Belouni, Mohamad. "Plans d'expérience optimaux en régression appliquée à la pharmacocinétique." Thesis, Grenoble, 2013. http://www.theses.fr/2013GRENM056/document.
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Le problème d'intérêt est d'estimer la fonction de concentration et l'aire sous la courbe (AUC) à travers l'estimation des paramètres d'un modèle de régression linéaire avec un processus d'erreur autocorrélé. On construit un estimateur linéaire sans biais simple de la courbe de concentration et de l'AUC. On montre que cet estimateur construit à partir d'un plan d'échantillonnage régulier approprié est asymptotiquement optimal dans le sens où il a exactement la même performance asymptotique que le meilleur estimateur linéaire sans biais (BLUE). De plus, on montre que le plan d'échantillonnage optimal est robuste par rapport à la misspecification de la fonction d'autocovariance suivant le critère du minimax. Lorsque des observations répétées sont disponibles, cet estimateur est consistant et a une distribution asymptotique normale. Les résultats obtenus sont généralisés au processus d'erreur de Hölder d'indice compris entre 0 et 2. Enfin, pour des tailles d'échantillonnage petites, un algorithme de recuit simulé est appliqué à un modèle pharmacocinétique avec des erreurs corréléesThe problem of interest is to estimate the concentration curve and the area under the curve (AUC) by estimating the parameters of a linear regression model with autocorrelated error process. We construct a simple linear unbiased estimator of the concentration curve and the AUC. We show that this estimator constructed from a sampling design generated by an appropriate density is asymptotically optimal in the sense that it has exactly the same asymptotic performance as the best linear unbiased estimator (BLUE). Moreover, we prove that the optimal design is robust with respect to a misspecification of the autocovariance function according to a minimax criterion. When repeated observations are available, this estimator is consistent and has an asymptotic normal distribution. All those results are extended to the error process of Hölder with index including between 0 and 2. Finally, for small sample sizes, a simulated annealing algorithm is applied to a pharmacokinetic model with correlated errors
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Guillet, Oliver. "Modélisation des corrélations spatiales d'erreurs d'observation en assimilation de données variationnelle : étude sur des maillages non structurés." Thesis, Toulouse, INPT, 2019. http://www.theses.fr/2019INPT0018.
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Dans cette thèse, nous proposons une classe de méthodes permettant de représenter numériquement les corrélations spatiales d’erreurs d’observation en assimilation de données variationnelle. Partant du lien existant entre les solutions de l’équation de diffusion implicite et les fonctions de corrélation de Matérn, nous construisons des opérateurs de corrélation et des opérateurs de corrélation inverses adaptés à la grande dimension. La discrétisation de l’équation de diffusion par la méthode des éléments finis permet de manipuler des données qui ne reposent pas nécessairement sur des maillages structurés, comme c’est le cas pour les observations satellites assimilées dans les modèles de météorologie. Les expériences sont menées en utilisant des données de l’imageur infrarouge Seviri dont les images contiennent notamment de fortes corrélations horizontales. Nous montrons que la qualité de notre modèle de corrélation peut dépendre localement de la distribution spatiale des observations. Néanmoins, l’introduction d’un maillage auxiliaire pour effectuer les calculs en éléments finis permet de s’affranchir de cette dépendance. Dans ce cas, la précision de la méthode s’acquiert au prix d’un opérateur inverse plus difficile à appliquer. Finalement, on propose des stratégies pour appliquer cet inverse efficacementIn this thesis, we propose a class of methods to represent spatial observation error correlations numerically in variational data assimilation. Based on the existing link between solutions of the time-implicit diffusion equation and Matérn correlation functions, we design correlation operators and inverse correlation operators that are appropriate for large datasets. Discretizing the diffusion equation with the finite element method allows us to account for data that do not necessarily lie on a structured mesh, as is the case with satellite observations assimilated in meteorology. Experiments are carried out using data from the infrared imager Seviri, the images of which are known for containing strong horizontal correlations. We show that the quality of our correlation model may depend locally on the spatial distribution of the observations. Nevertheless, by introducing an auxiliary mesh to perform the finite element computations, we can control this dependency to a large extent. Improving the accuracy of the method this way comes at the expense of making the inverse correlation operator more complicated. Finally, strategies for efficiently modelling the inverse of the correlation operator are proposed
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Rezazadeh, Arezou. "Error exponent analysis for the multiple access channel with correlated sources." Doctoral thesis, Universitat Pompeu Fabra, 2019. http://hdl.handle.net/10803/667611.
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Due to delay constraints of modern communication systems, studying reliable communication with finite-length codewords is much needed. Error exponents are one approach to study the finite-length regime from the information-theoretic point of view. In this thesis, we study the achievable exponent for single-user communication and also multiple-access channel with both independent and correlated sources. By studying different coding schemes including independent and identically distributed, independent and conditionally distributed, message-dependent, generalized constant-composition and conditional constant-composition ensembles, we derive a number of achievable exponents for both single-user and multi-user communication, and we analyze them.A causa de les restriccions de retard dels sistemes de comunicació moderns, estudiar la fiabilitat de la comunicació amb paraules de codis de longitud finita és important. Els exponents d’error són un mètode per estudiar el règim de longitud finita des del punt de vista de la teoria de la informació. En aquesta tesi, ens centrem en assolir l’exponent per a la comunicació d’un sol usuari i també per l’accés múltiple amb fonts independents i correlacionades. En estudiar els següents esquemes de codificació amb paraules independents i idènticament distribuïdes, independents i condicionalment distribuïdes, depenent del missatge, composició constant generalitzada, i conjunts de composició constant condicional, obtenim i analitzem diversos exponents d’error assolibles tant per a la comunicació d’un sol usuari com per la de múltiples usuaris.
Las restricciones cada vez más fuertes en el retraso de transmisión de los sistemas de comunicación modernos hacen necesario estudiar la fiabilidad de la comunicación con palabras de códigos de longitud finita. Los exponentes de error son un método para estudiar el régimen de longitud finita desde el punto de vista la teoría de la información. En esta tesis, nos centramos en calcular el exponente para la comunicación tanto de un solo usuario como para el acceso múltiple con fuentes independientes y correladas. Estudiando diferentes familias de codificación, como son esquemas independientes e idénticamente distribuidos, independientes y condicionalmente distribuidos, que dependen del mensaje, de composición constante generalizada, y conjuntos de composición constante condicional, obtenemos y analizamos varios exponentes alcanzables tanto para la comunicación de un solo usuario como para la de múltiples usuarios.
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Michels, Karin Brigitte. "The effect of correlated measurement error in multivariate models of diet." Thesis, University of Cambridge, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.616174.
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Bijsterbosch, Janine. "Behavioural and neural correlates of sensorimotor timing and error correction." Thesis, University of Sheffield, 2011. http://etheses.whiterose.ac.uk/2008/.
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Timing is essential for human movement and cognition and is affected in many psychiatric and neurological disorders. The aim of this thesis was to determine the behavioural and neural correlates of sensorimotor timing and of temporal error correction. Motor timing can be studied using a sensorimotor synchronization (SMS) task. In SMS, timing accuracy is assessed during synchronized finger tapping with a regular pacing stimulus and error correction performance is measured based on responses following induced local timing shifts. Study one addressed the effects of task-related and subject-specific factors on SMS performance and showed that tapping variability was reduced during bimanual SMS, compared with unimanual SMS. Study two examined the role of the primary and pre-motor cortices in SMS using theta burst transcranial magnetic stimulation (TBS). The findings suggested that the left-lateralized pre-motor cortex may play a role in temporal error correction. This hypothesis was tested in study three which confirmed that suppression TBS over the left pre-motor significantly affected error correction responses following supraliminal timing shifts. Study four used functional magnetic resonance imaging (fMRI) to determine the neural correlates of timing and error correction. It was shown that connectivity emerges in a cortico- cerebellar network including the left-lateralized cerebellum and frontal regions during the correction of supraliminal timing shifts. Study five further examined the role of functional connectivity using fMRI and revealed that interhemispheric connectivity between the primary motor cortices was significantly greater during bimanual SMS, compared with unimanual SMS. Lastly, studies six and seven addressed the efficacy of TBS and showed that the local distribution of subarachnoid cerebrospinal fluid can significantly alter TBS-induced stimulation. In the general discussion it is suggested that sensorimotor timing and error correction may be achieved using internal feedforward models in the cerebellum that inform movement initiation controlled by the left pre-motor cortex.
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Lu, Feng. "Studies of a quantum scheduling algorithm and on quantum error correction." Doctoral diss., University of Central Florida, 2007. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3540.
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Quantum computation has been a rich field of study for decades because it promises possible spectacular advances, some of which may run counter to our classically rooted intuitions. At the same time, quantum computation is still in its infancy in both theoretical and practical areas. Efficient quantum algorithms are very limited in number and scope; no real breakthrough has yet been achieved in physical implementations. Grover's search algorithm can be applied to a wide range of problems; even problems not generally regarded as searching problems can be reformulated to take advantage of quantum parallelism and entanglement leading to algorithms which show a square root speedup over their classical counterparts. This dissertation discusses a systematic way to formulate such problems and gives as an example a quantum scheduling algorithm for an R||C_max problem. This thesis shows that quantum solution to such problems is not only feasible but in some cases advantageous. The complexity of the error correction circuitry forces us to design quantum error correction codes capable of correcting only a single error per error correction cycle. Yet, time-correlated errors are common for physical implementations of quantum systems; an error corrected during a certain cycle may reoccur in a later cycle due to physical processes specific to each physical implementation of the qubits. This dissertation discusses quantum error correction for a restricted class of time-correlated errors in a spin-boson model. The algorithm proposed allows the correction of two errors per error correction cycle, provided that one of them is time-correlated. The algorithm can be applied to any stabilizer code, perfect or non-perfect, and simplified the circuit complexity significantly comparing to the classic quantum error correction codes.Ph.D.
School of Electrical Engineering and Computer Science
Engineering and Computer Science
Computer Science PhD
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Tong, Hui. "A joint data rate - error rate analysis in correlated space-time-wireless channels /." Available online. Click here, 2007. http://sunshine.lib.mtu.edu/ETD/DISS/2007/Electrical&ComputerEng/tongh/diss.pdf.
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López, Delgado Daniel Antonio 1987. "Threshold theorem for a quantum memory in a correlated environment : Teorema do limiar para uma memória quântica em um ambiente correlacionado." [s.n.], 2016. http://repositorio.unicamp.br/jspui/handle/REPOSIP/321757.
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Orientadores: Amir Ordacgi Caldeira, Eduardo Peres Novais de SáTese (doutorado) - Universidade Estadual de Campinas, Instituto de Física Gleb Wataghin
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Resumo: A criação de um computador quântico é um projeto que guia, ao mesmo tempo, avanços tecnológicos e um melhor entendimento das propriedades de sistemas quânticos e da Mecânica Quântica em geral. O teorema do limiar é derivado da teoria quântica de correção de erros e garante que, se o ruido estocástico que afeta os componentes de um computador quântico encontra-se abaixo de um valor limite, podemos operar esse computador quântico confiavelmente. Investigamos como esse teorema é modificado quando consideramos uma memória quântica (a qual usa o código de superfície para corrigir erros) acoplada a um ambiente correlacionado. O limiar de erros nesse caso é relacionado à transição de fase ordem-desordem de um sistema de spin equivalente
Abstract: The design of a quantum computer is a project which drives, at the same time, technological advancement and a better understanding of the properties of quantum systems and of Quantum Mechanics in general. The threshold theorem comes from quantum error correction theory and it guarantees that, if stochastic noise affecting the components of a quantum computer is below some threshold value, we can operate this quantum computer reliably. We investigate how this theorem is modified when we consider a quantum memory (which uses the surface code to correct errors) coupled to a correlated environment. The error threshold in this case is related the order-disorder phase transition of an equivalent spin system
Doutorado
Física
Doutor em Ciências
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Seedorff, Michael Thomas. "Methods for testing for group differences in highly correlated, nonlinear eye-tracking data." Diss., University of Iowa, 2018. https://ir.uiowa.edu/etd/6279.
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Data resulting from eye-tracking experiments allows researchers to analyze the decision making process as study participants consider alternative items prior to the ultimate end point selection. The aim of such an analysis is to extract the underlying cognitive decision making process that develops throughout the experiment. Resulting data can be difficult to analyze, however, as eye-tracking curves have very high autocorrelation values which consists of measurements that are milliseconds apart, as mandated by the nature of eye movements. We propose an analytic approach to eye-tracking data that tests for statistically significant differences at every time point along the curve while calculating an appropriate familywise error rate correction which is based upon an autoregressive correlation assumption of the test statistics. Our technique has been implemented in the R package BDOTS with various extensions relevant to the real-world analysis of highly correlated nonlinear data. A popular alternative approach to analyzing eye-tracking data is to fit mixed models to the area under the curve. Through simulation studies we provide evidence for the benefit of using information criterion measures in selection of the random effects structure and make an argument against current industry-standard approaches such as sequential likelihood ratio tests or always using a maximal random effects structure.
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Dube, Tina Juliet Thandeka. "Assessing and correcting the effects of measurement error among correlated covariates in a poroportional hazards setting." Thesis, Birmingham, Ala. : University of Alabama at Birmingham, 2008. https://www.mhsl.uab.edu/dt/2009r/dube.pdf.
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Betaille, David Francois. "Assessment and improvement of the capabilities of a window correlator to model GPS multipath phase errors." Thesis, University College London (University of London), 2004. http://discovery.ucl.ac.uk/1446495/.
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This thesis is concerned with the modelling of Global Positioning System (GPS) phase multipath. GPS is increasingly used for very high precision (centimetre level) engineering surveying applications such as setting out on construction sites and the control of major civil engineering plant (e.g. bulldozers, graders and pavement layers). In such applications the phase of the carrier signal is the basic observable and the dominant error source is muldpath (electromagnetic reflections of the carrier waves from surfaces in the surroundings of the antennas). The work contained in the thesis has been carried out in collaboration with the LCPC (Laboratoire Central des Ponts et Chaussees) in Nantes, France, which made available its test facility and Leica Geosystems, Heerbrugg, Switzerland, a GPS manufacmrer, which funded the work and which made available modified equipment for testing. The specific subject of the research is the assessment and improvement of the capabilities of a Phase Multipath Mitigation Window correlator (PMMW) to model GPS multipath phase errors. The phase window correlator is a new sampling technique dedicated to the estimation of multipath errors in phase measurements. The thesis contains background material on GPS multipath mitigation and on several existing patents related to the PMMW technique. The main contribution of the work relates to:The rigorous mathematical modelling of multipath, starting from the physics of the phenomenon, right through to the phase measurement process itself, particularly that based on the PMMW correlator. The design of a general testing methodology in a controlled environment to assess the efficacy of multipath mitigation techniques. The carrying out of full-scale experiments at the LCPC in both static and kinematic modes and the assessment of the performances and limitations of the PMMW correlator. Initial investigations into the design of a new real-time correction strategy for phase multipath phase errors based on a combination of multipath observables including the signal-to-noise ratio, the output from the PMMW correlator and an estimation of the code multipath errors from dual frequency phase data. A key feature of the new strategy is its ability to overcome the major limitation of the PMMW technique, i.e. its insensitivity to multipath caused by very close reflectors. It enables the multipath corrupted phase measurements to be improved by 10 % in average in this case, whereas the PMMW corrections on their own had almost no effect.
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Iyer, Vipin V. "Face Milling Simulation to Correlate and Predict The Effects of Machine Tool Geometric Errors on Part Flatness Tolerance." University of Cincinnati / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1406881376.
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Herrojo, Ruiz María del Carmen. "Electrophysiological Correlates of Motor Control and Error-Monitoring in Healthy Pianists and Pianists with Musician's Dystonia." Hannover Bibliothek der Tierärztlichen Hochschule Hannover, 2009. http://d-nb.info/1000116883/34.
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Jiao, Yuanfang. "A simulation comparison of two methods for controlling the experiment-wise Type I error rate of correlated tests for contrasts in one-way completely randomized designs." Kansas State University, 2014. http://hdl.handle.net/2097/17619.
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Master of ScienceDepartment of Statistics
Paul I. Nelson
A Bonferroni and an ordered P-value solution to the problem of controlling the experiment-wise Type I error rate are studied and compared in terms of actual size and power when carrying out correlated tests. Although both of these solutions can be used in a wide variety of settings, here they are only investigated in the context of multiple testing that specified pairwise comparisons of means, selected before data are collected, are all equal to zero in a completely randomized, balanced, one factor design where the data are independent random samples from normal distributions all having the same variance. Simulations indicate that both methods are very similar and effective in controlling experiment wise type error at a nominal rate of 0.05. Because the ordered P-value method has, almost uniformly, slightly greater power, it is my recommendation for use in the setting of this report.
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Schreiber, Melanie. "Alterations of electrophysiological correlates of performance monitoring with age." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2012. http://dx.doi.org/10.18452/16641.
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Die zugrunde liegenden Prozesse altersbedingter Veränderungen exekutiver Funktionen werden vielfach untersucht. Für eine flexible Anpassung ist die Überwachung von Handlungen und deren Konsequenzen notwendig. Handlungsüberwachung wird mit ereigniskorrelierten Potentialen (EKP) wie der error-related negativity/error negativity (ERN/Ne) und der correct-related negativity/correct negativity (CRN) gemessen. Die Arbeit untersucht die Handlungsüberwachung bei jüngeren und älteren Erwachsenen mit dem Ziel, das Wissen über kompensatorische Strategien bei Älteren und deren Auswirkung auf die EKP Befunde zu erweitern. Ältere zeigten reduzierte ERN/Ne und größere oder vergleichbar große CRN Amplituden im Vergleich zu Jüngeren. Während nur die Jüngeren eine Reduktion der ERN/Ne mit größerer Aufgabenschwierigkeit zeigten, zeigten beide Gruppen eine ERN/Ne Reduktion unter der Instruktion, die Geschwindigkeit anstatt Genauigkeit erforderte. Nur bei Jüngeren variierte die CRN mit der Kompatibilität der Trials, mit der Aufgabenschwierigkeit und Instruktion. Ältere wiesen geringere Fehlerraten und längere Reaktionszeiten als Jüngere auf. Dieses Muster deutet auf eine kompensatorische oder strategische Anpassung in Folge von Defiziten in der Nutzung einer erfolgreichen Kombination von proaktiver und reaktiver Kontrolle hin. Es wird postuliert, dass ERN/Ne und CRN einen gemeinsamen Prozess darstellen, der allgemeine Überwachungsfunktionen reflektiert. Die ERN/Ne beinhaltet zusätzlich einen Prozess, der Fehlerüberwachung signalisiert. Daraus ergibt sich die Vermutung, dass die reduzierte ERN/Ne bei Älteren entweder auf eine Verringerung spezifischer Fehlerprozesse oder auf eine Beeinträchtigung allgemeiner Überwachungsfunktionen zurückzuführen ist. Altersbezogene Veränderungen der EKP Befunde könnten den veränderten Einsatz von kompensatorischer Kontrolle bei Älteren im Vergleich zu Jüngeren reflektieren. Dieser Frage sollte in zukünftigen Studien nachgegangen werden.Executive functions decline with age and a growing body of research aims at investigating age-related changes of the underlying processes. One important function is to monitor actions and action outcomes, which is necessary for flexible adjustments and learning. This so-called performance monitoring can be measured with event-related potentials (ERP), namely the error-related negativity/error negativity (ERN/Ne) and the correct-related negativity/correct negativity (CRN). This work examined performance monitoring in younger and older adults with the aim to advance knowledge about compensatory strategies in older adults and their implications for ERP results. Findings revealed reduced ERN/Ne and larger or similar-sized CRN in older compared to younger adults. While only younger adults showed a decrease of ERN/Ne with higher task difficulty, both age groups showed a reduction of ERN/Ne in the speed compared to the accuracy condition. Additionally, only younger adults showed variations, in that the CRN was smaller for compatible compared to incompatible trials, in the easy compared to the difficult condition, and in the speed compared to the accuracy condition. Behaviorally, older adults had less errors and longer response latencies than younger adults. This pattern may reflect compensatory or strategic adjustments with age which may be due to deficits in the use of a successful combination of proactive and reactive control. It was further assumed that ERN/Ne and CRN share a common process that reflects general monitoring functions and ERN/Ne includes an additional process that reflects error-specific monitoring. Accordingly, the ERN/Ne attenuation in older adults is either caused by reduced error-specific processing or compromised general monitoring functions. Age-related changes in ERP findings indicate altered engagement of compensatory cognitive control in older compared to younger adults. However, this question has to be further clarified in future studies.
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Bosse, Anna L. "Comparing the Structural Components Variance Estimator and U-Statistics Variance Estimator When Assessing the Difference Between Correlated AUCs with Finite Samples." VCU Scholars Compass, 2017. https://scholarscompass.vcu.edu/etd/5194.
Full textAbstract:
Introduction: The structural components variance estimator proposed by DeLong et al. (1988) is a popular approach used when comparing two correlated AUCs. However, this variance estimator is biased and could be problematic with small sample sizes.
Methods: A U-statistics based variance estimator approach is presented and compared with the structural components variance estimator through a large-scale simulation study under different finite-sample size configurations.
Results: The U-statistics variance estimator was unbiased for the true variance of the difference between correlated AUCs regardless of the sample size and had lower RMSE than the structural components variance estimator, providing better type 1 error control and larger power. The structural components variance estimator provided increasingly biased variance estimates as the correlation between biomarkers increased.
Discussion: When comparing two correlated AUCs, it is recommended that the U-Statistics variance estimator be used whenever possible, especially for finite sample sizes and highly correlated biomarkers.
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Herrojo, Ruiz María del Carmen [Verfasser]. "Electrophysiological Correlates of Motor Control and Error-Monitoring in Healthy Pianists and Pianists with Musician's Dystonia / María del Carmen Herrojo Ruiz." Hannover : Bibliothek der Tierärztlichen Hochschule Hannover, 2009. http://d-nb.info/1000116883/34.
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Fingleton, Bernard, and Manfred M. Fischer. "Neoclassical theory versus new economic geography. Competing explanations of cross-regional variation in economic development." WU Vienna University of Economics and Business, 2008. http://epub.wu.ac.at/3955/1/SSRN%2Did1111590.pdf.
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This paper uses data for 255 NUTS-2 European regions over the period 1995-2003
to test the relative explanatory performance of two important rival theories seeking to explain
variations in the level of economic development across regions, namely the neoclassical
model originating from the work of Solow (1956) and the so-called Wage Equation, which is
one of a set of simultaneous equations consistent with the short-run equilibrium of new
economic geography (NEG) theory, as described by Fujita, Krugman and Venables (1999).
The rivals are non-nested, so that testing is accomplished both by fitting the reduced form
models individually and by simply combining the two rivals to create a composite model in an
attempt to identify the dominant theory. We use different estimators for the resulting panel
data model to account variously for interregional heterogeneity, endogeneity, and temporal
and spatial dependence, including maximum likelihood with and without fixed effects, two
stage least squares and feasible generalised spatial two stage least squares plus GMM; also
most of these models embody a spatial autoregressive error process. These show that the
estimated NEG model parameters correspond to theoretical expectation, whereas the
parameter estimates derived from the neoclassical model reduced form are sometimes
insignificant or take on counterintuitive signs. This casts doubt on the appropriateness of
neoclassical theory as a basis for explaining cross-regional variation in economic
development in Europe, whereas NEG theory seems to hold in the face of competition from
its rival. (authors' abstract)
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Lau, Buon Kiong. "Applications of Adaptive Antennas in Third-Generation Mobile Communications Systems." Curtin University of Technology, Australian Telecommunications Research Institute, 2002. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=12983.
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Adaptive antenna systems (AAS's) are traditionally of interest only in radar and sonar applications. However, since the onset of the explosive growth in demand for wireless communications during the 1990's, researchers are giving increasing attention to the use of AAS technology to overcome practical challenges in providing the service. The main benefit of the technology lies in its ability to exploit the spatial domain, on top of the temporal and frequency domains, to improve on transceiver performance. This thesis presents a unified study on two classes of preprocessing techniques for uniform circular arrays (UCA's). UCA's are of interest because of their natural ability to provide a full azimuth (i.e. 360') coverage found in typical scenarios for sensor array applications, such as radar, sonar and wireless communications. The two classes of preprocessing techniques studied are the Davies transformation and the interpolated array transformations. These techniques yield a mathematically more convenient form - the Vandermonde form - for the array steering vector via a linear transformation. The Vandermonde form is useful for different applications such as direction-of-arrival (DOA) estimation and optimum or minimum variance distortionless response (MVDR) beamforming in correlated signal environment and beampattem synthesis. A novel interpolated array transformation is proposed to overcome limitations in the existing interpolated array transformations. A disadvantage of the two classes of preprocessing techniques for UCA's with omnidirectional elements is the lack of robustness in the transformed array steering vector to array imperfections under certain conditions. In order to mitigate the robustness problem, optimisation problems are formulated to modify the transformation matrices.Suitable optimisation techniques are then applied to obtain more robust transformations. The improved transformations are shown to improve robustness but at the cost of larger transformation errors. The benefits of the robustification procedure are most apparent in DOA estimation. In addition to the algorithm level studies, the thesis also investigates the use of AAS technology with respect to two different third generation (3G) mobile communications systems: Enhanced Data rates for Global Evolution (EDGE) and Wideband Code Division Multiple Access (WCDMA). EDGE, or more generally GSM/EDGE Radio Access Network (GERAN), is the evolution of the widely successful GSM system to provide 3G mobile services in the existing radio spectrum. It builds on the TDMA technology of GSM and relies on improved coding and higher order modulation schemes to provide packet-based services at high data rates. WCDMA, on the other hand, is based on CDMA technology and is specially designed and streamlined for 3G mobile services. For WCDMA, a single-user approach to DOA estimation which utilises the user spreading code and the pulse-shaped chip waveform is proposed. It is shown that the proposed approach produces promising performance improvements. The studies with EDGE are concerned with the evaluation of a simple AAS at the system and link levels.
Results from, the system and link level simulations are presented to demonstrate the effectiveness of AAS technology in the new mobile communications system. Finally, it is noted that the WCDMA and EDGE link level simulations employ the newly developed COST259 directional channel model, which is capable of producing accurate channel realisations of macrocell environments for the evaluation of AAS's.
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"Optimal Design of Experiments Subject to Correlated Errors." Department of Statistics and Mathematics, 2000. http://epub.wu-wien.ac.at/dyn/dl/wp/epub-wu-01_a47.
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Ghement, Isabella Rodica. "Inference in partially linear models with correlated errors." Thesis, 2005. http://hdl.handle.net/2429/16950.
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We study the problem of performing statistical inference on the linear effects in partially
linear models with correlated errors. To estimate these effects, we introduce usual, modified
and estimated modified backfitting estimators, relying on locally linear regression.
We obtain explicit expressions for the conditional asymptotic bias and variance of the
usual backfitting estimators under the assumption that the model errors follow a mean
zero, covariance-stationary process. We derive similar results for the modified backfitting
estimators under the more restrictive assumption that the model errors follow a mean
zero, stationary autoregressive process of finite order. Our results assume that the width
of the smoothing window used in locally linear regression decreases at a specified rate,
and the number of data points in this window increases. These results indicate that the
squared bias of the considered estimators can dominate their variance in the presence of
correlation between the linear and non-linear variables in the model, therefore compromising
their i/n-consistency. We suggest that this problem can be remedied by selecting
an appropriate rate of convergence for the smoothing parameter of the-estimators. We
argue that this rate is slower than the rate that is optimal for estimating the non-linear
effect, and as such it 'undersmooths' the estimated non-linear effect. For this reason,
data-driven methods devised for accurate estimation of the non-linear effect may fail to
yield a satisfactory choice of smoothing for estimating the linear effects. We introduce
three data-driven methods for accurate estimation of the linear effects. Two of these
methods are modifications of the Empirical Bias Bandwidth Selection method of Opsomer
and Ruppert (1999). The third method is a non-asymptotic plug-in method. We
use the data-driven choices of smoothing supplied by these methods as a basis for constructing
approximate confidence intervals and tests of hypotheses for the linear effects.
Our inferential procedures do not account for the uncertainty associated with the fact
that the choices of smoothing are data-dependent and the error correlation structure is
estimated from the data. We investigate the finite sample properties of our procedures
via a simulation study. We also apply these procedures to the analysis of data collected
in a time-series air pollution study.Science, Faculty of
Statistics, Department of
Graduate
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Demirhan, Eren. "Variable selection for multivariate smoothing splines with correlated random errors." 2008. http://www.lib.ncsu.edu/theses/available/etd-07222008-093940/unrestricted/etd.pdf.
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Yuan, Tzu-Lun, and 袁子倫. "On some optimal design problems for response surface model with correlated errors." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/7tntkf.
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博士國立中山大學
應用數學系研究所
107
Experiments performed with good designs on the settings of controllable factors are essential collecting useful information efficiently and may provide the precise estimation of statistical modeling and corresponding inferences. In the first part of this dissertation, our main interest is to investigate the design problems for first- and second- order response surface models (RSMs) with correlated errors and related applications. Under the first- and second- order RSMs with fixed effects and correlated errors, we investigate the D-optimal designs for estimation of the unknown parameters in the RSMs, for two explanatory variables. The design region is considered to be within a circle and the correlation between two observations depends on the distance of the two design points. We present analytical minimally supported D-optimal design results, and numerical D-optimal designs for circular design region with spatially correlated error structure. On the other hand, the main idea of RSM is to use certain experimental procedures to search for control variables of an optimal response sequentially in an experiment. Based on such an idea, we would like to find designs optimal for estimation and prediction on the nonlinear models, used to describe the behaviors of signals obtained from various differential pad placement designs of a capacitive coupling based stacked die package. In the second part of this dissertation, we provide parametric models under different pad sizes to exhibit the patterns of the SNR values versus the frequencies for various die placement designs with given pitch distance and overlapping percentage. In the end, we use an approach analogous to the response surface methodology to find the optimal design configuration for each pad size with an optimal response.
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Rosales, Marticorena Luis Francisco. "Empirical Bayesian Smoothing Splines for Signals with Correlated Errors: Methods and Applications." Doctoral thesis, 2016. http://hdl.handle.net/11858/00-1735-0000-0028-87F9-6.
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St-Aubin, Robert. "Smoothing parameter selection when errors are correlated and application to ozone data." Thesis, 1998. http://hdl.handle.net/2429/8250.
Full textAbstract:
Automatic smoothing parameter selection methods for nonparametric regression
like cross-validation and generalized cross-validation are known to be
severely affected by dependence in the regression errors. We proposed, in
this work, to modify some of the ideas used in the cross-validation criterion in
kernel regression with dependent errors and apply them to smoothing splines
with model based penalty. Model based penalty smoothing permits us to keep
the flexibility of the nonparametric methods while it also allows us to specify
a favoured parametric model which can help improve on the estimate of the
regression function.
We consider the "modified cross-validation" (also known as Leave—21+1
out) and the "blockwise cross-validation" smoothing parameter selection techniques
which were initially proposed by Hardle and Vieu (1992) and Wehrly
and Hart (1988) respectively. These two smoothing parameter selection techniques
take correlation into account and alleviate its effect on the regression
function estimation.
We use a simulation study to evaluate the performance of our two
smoothing parameter selection techniques. We compare the results with a few commonly used parametric techniques. Our techniques are also applied to
an air pollution data set where we estimate the underlying trend of daily and
monthly ground ozone levels in southern Ontario.
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Hsu, Yao-chung, and 許耀中. "Minimally Supported D-optimal Designs for Response Surface Models with Spatially Correlated Errors." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/00308011139181529380.
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碩士國立中山大學
應用數學系研究所
100
In this work minimally supported D-optimal designs for response surface models with spatially correlated errors are studied. The spatially correlated errors describe the correlation between two measurements depending on their distance d through the covariance function C(d)=exp(-rd). In one dimensional design space, the minimally supported D-optimal designs for polynomial models with spatially correlated errors include two end points and are symmetric to the center of the design region. Exact solutions for simple linear and quadratic regression models are presented. For models with third or higher order, numerical solutions are given. While in two dimensional design space, the minimally supported D-optimal designs are invariant under translation、rotation and reflection. Numerical results show that a regular triangle on the experimental region of a circle is a minimally supported D-optimal design for the first-order response surface model.
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Lee, Pin-Yi, and 李品毅. "Using parallel programming paradigms to reduce errors of correlated simulation in estimation and scheduling." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/mn5w38.
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碩士國立臺灣科技大學
營建工程系
99
The success of a construction project can be determined by aspects of its scheduling , costs and quality. Its quality standards have already been specified the moment the contract is signed. Therefore, how to plan the schedule and control the costs have become an important issue in project management. In a construction project individual operations often have some correlation with one another. For example, the delay in operation time will cause the costs to increase.However, when material cost increases,it influences the costs of all the related activities. Therefore, if the correlation between time and cost is ignored, there is a possibility in giving a inaccurate evaluation. It is necessary to quantify the correlations between operations to obtain more accurate estimation. fter the correlations are determined,they can be used o conduct simulations through NORmal To Anything (NORTA) and Iman and Conover(IC) to develop a cost estimation or schedule prediction.During the process,Cholesky factorization is needed to conduct a correlation simulation.But in situations when the original correlation matrix is not positive definite,the Cholesky factorization will generate imaginary roots,thus causing the simulation to fail.Evan thought many scholars have already presented methods to adjust the correlation matrix,the modified matrix causes inaccuracy is cost estimale and schedule prediction. Therefore, this study uses particl swarm optimizstion (PSO)to search for a feasible correlation matrix, which after correlation simulation will lead to minimum error.Since PSO and cooelation simulation are both computational expensive,this study investigates the use of a computer cluster and three parallel progrmming strategies in reducing computatial time.
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Peng, Pin-Rui, and 彭品叡. "Identifying essence codings and efffects in functional linear models with heterogeneous and correlated errors." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/hdj6sw.
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Liao, Chang-Kai, and 廖昶凱. "The Power of Lee Test (1998) When the Stochastic Coefficient and Errors are Correlated." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/3q8244.
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碩士國立中山大學
經濟學研究所
107
The main purpose of this paper is to continue to explore the results of Su and Roca (2012).The correlation between the error term and the random coefficient of Lee’s statistical formula will lead to a a change in the verification force.We use the methodof partial heterogeneity hyprothsis of McCabe and Smith(1988) and join the correlation coefficient between the random coefficient and the error is derived,and the distribution is derived.It is found that the distribution is divergent at the rate of one quarter of the number of samples. Under such allocation,the increase of the number of samples will increase the verification force ,and observe the distribution result.The correction between the error term and the random coefficient will have the same effect,and the simulation will be carried out in the simulation.It can be seen that the divergence effent mainly occours in the form of the variance number,which leads to an increase in the verification force,but the increase is limited. Keywords: stochastic unit root (STUR) test; Wiener process; the sequence of local alternatives; weak convergence; difference stationary. iii
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Hsieh, Yi-Fang, and 謝宜芳. "The Power of Distaso (2008) Test When the Stochastic Coefficient and Errors are Correlated." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/64fb53.
Full textAbstract:
碩士國立中山大學
經濟學研究所
107
Unit root test has always been an important issue in time series data analysis. Based on the ALM test of Distaso (2008), this paper makes the random coefficient and the error term have the correlation, derives the limit distribution of the ALM test under the alternative hypothesis and uses Monte Carlo simulation to verification. The study found that under the correlation between random coefficients and error terms, the ALM test needs to be divided by two-thirds of the sample number to converge to the limit distribution, so when the number of samples increases, the power of ALM test will increases. In addition, it is found that both the correlation coefficient of the random coefficient and the error term or the variance of the random coefficient increase, which also increases the power of the ALM test.
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"Further aspects on an example of D-optimal designs in the case of correlated errors." Institut für Statistik und Mathematik, 2004. http://epub.wu-wien.ac.at/dyn/dl/wp/epub-wu-01_6db.
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Chen, I.-Po, and 陳易伯. "The Power of McCabe and Tremayne Test (1995) for Difference Stationarity When the Errors are Correlated." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/zccrve.
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碩士國立中山大學
經濟學研究所
107
In this thesis, I relax McCabe and Smith (1998)’s assumptions to reconsider the power properties of McCabe and Tremayne (1995, MT) test for the difference stationarity of a times series. Without the independence assumption between the random coefficient and error process as that of McCabe and Smith (1998) , I derive the asymptotic distribution of MT test under local heteroscedastic integration alternative. I find that the MT test statistics is O(T1/4) and therefore it is diverge. In a finite sample, the power increase as the correlation or the variance of error process increase. Monte Carlo evidence supports our theoretical findings.
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Chang, Min-Han, and 張民翰. "A Phase II Multivariate Exponentially Weighted Moving Average Monitoring Scheme for Nonlinear Random-Effects Profiles with Correlated Errors." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/64008304607254140037.
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碩士國立交通大學
統計學研究所
102
The technique of control charts for monitoring the quality of products is used in the modern business, chemistry, manufacturing, etc. It characterizes one or more quality characteristics of products to monitor a process. In the literature, it is commonly assumed that observations are independent within each profile; however, this assumption is inappropriate in many actual situations and thus a Phase II multivariate exponentially weighted moving average monitoring scheme for nonlinear random-effects profiles with correlated errors is proposed in the paper. A real data set in Walker and Wright (2002) and a simulation study are utilized to illustrate the usefulness and applicability of the proposed methodology.
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ZIAO, MENG-PING, and 蕭夢萍. "Combined analysis of two split-split plot design in randomized block layout with correlated errors and unequal number of sub-subtreatment levels." Thesis, 1992. http://ndltd.ncl.edu.tw/handle/48715837015769318091.
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