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This thesis advocates the use of maximum likelihood analysis for generalized regression models with measurement error in a single explanatory variable. This will be done first by presenting a computational algorithm and the numerical details for carrying out this algorithm on a wide variety of models. The computational methods will be based on the EM algorithm in conjunction with the use of Gauss-Hermite quadrature to approximate integrals in the E-step. Second, this thesis will demonstrate the relative superiority of likelihood-ratio tests and confidence intervals over those based on asymptotic normality of estimates and standard errors, and that likelihood methods may be more robust in these situations than previously thought. The ability to carry out likelihood analysis under a wide range of distributional assumptions, along with the advantages of likelihood ratio inference and the encouraging robustness results make likelihood analysis a practical option worth considering in regression problems with explanatory variable measurement error. / Graduation date: 1999

Thesis (Ph.D.)--University of Delaware, 2009. / Principal faculty advisor: Wenbo Li, Dept. of Mathematical Sciences. Includes bibliographical references.

Thesis (Ph. D.)--Virginia Polytechnic Institute and State University, 1993. / Vita. Abstract. Includes bibliographical references (leaves 152-156). Also available via the Internet.

by Sze Tsz-leung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1993. / Includes bibliographical references (leaves 91). / Chapter Chapter 1 --- Introduction / Chapter 1.1 --- Basic concepts of Monte Carlo integration --- p.1 / Chapter 1.1.1 --- Importance sampling --- p.4 / Chapter 1.1.2 --- Control variate --- p.5 / Chapter 1.1.3 --- Antithetic variate --- p.6 / Chapter 1.1.4 --- Stratified sampling --- p.7 / Chapter 1.1.5 --- Biased Estimator --- p.10 / Chapter 1.2 --- Some special methods in Monte Carlo integration --- p.11 / Chapter 1.2.1 --- Haber´ةs modified Monte Carlo quadrature I --- p.11 / Chapter 1.2.2 --- Haber's modified Monte Carlo quadrature II --- p.11 / Chapter 1.2.3 --- Weighted Monte Carlo integration --- p.12 / Chapter 1.2.4 --- Adaptive importance sampling --- p.13 / Chapter Chapter 2 --- New methods / Chapter 2.1 --- The use of Newton Cotes quadrature formulae in stage one --- p.17 / Chapter 2.1.1 --- Using one-dimensional trapezoidal rule --- p.17 / Chapter 2.1.2 --- Using two-dimensional or higher dimensional product trapezoidal rule --- p.21 / Chapter 2.1.3 --- Extension to higher order one-dimensional Newton Cotes formulae --- p.32 / Chapter 2.2 --- The use of Guass quadrature rule in stage one --- p.45 / Chapter 2.3 --- Some variations of the new methods --- p.56 / Chapter 2.3.1 --- Using probability points in both stages --- p.56 / Chapter 2.3.2 --- Importance sampling --- p.59 / Chapter 2.3.2.1 --- Triangular distribution --- p.60 / Chapter 2.3.2.2 --- Beta distribution --- p.64 / Chapter Chapter 3 --- Examples / Chapter 3.1 --- Example one: using trapezoidal rule as basic rule --- p.73 / Chapter 3.1.1 --- One-dimensional case --- p.73 / Chapter 3.1.2 --- Two-dimensional case --- p.80 / Chapter 3.2 --- Example two: Using Simpson's 3/8 rule as basic rule --- p.85 / Chapter 3.3 --- Example three： Using Guass rule as basic rule --- p.86 / Chapter Chapter 4 --- Conclusion and discussions --- p.88 / Reference --- p.91

This thesis considers likelihood inferences for generalized linear models with additional random effects. The likelihood function involved ordinarily cannot be evaluated in closed form and numerical integration is needed. The theme of the thesis is a closed-form approximation based on Laplace's method. We first consider a special yet important case of the above general setting -- the Mantel-Haenszel-type model with overdispersion. It is seen that the Laplace approximation is very accurate for likelihood inferences in that setting. The approach and results on accuracy apply directly to the more general setting involving multiple parameters and covariates. Attention is then given to how to maximize out nuisance parameters to obtain the profile likelihood function for parameters of interest. In evaluating the accuracy of the Laplace approximation, we utilized Gauss-Hermite quadrature. Although this is commonly used, it was found that in practice inadequate thought has been given to the implementation. A systematic method is proposed for transforming the variable of integration to ensure that the Gauss-Hermite quadrature is effective. We found that under this approach the Laplace approximation is a special case of the Gauss-Hermite quadrature. / Graduation date: 1994

This dissertation presents a self-tuning regulator (STR) design method developed based upon a state-space linear quadratic Gaussian (LQG) control strategy for rejecting a disturbance in a flexible structure in the face of model uncertainty. The parameters to be tuned are treated as additional state variables and are estimated recursively together with the system state that is needed for feedback. Also, the feedback gains are designed in the LQ framework based upon the estimated model parameters. Two problems concerning the uncertainty of model parameters are recognized. First, we consider the uncertainty in the system matrix of the state space model. The self-tuning regulator is implemented by computer and the control law is obtained based upon a discrete-time model; however, only selected continuous-time parameters with physical meanings to which the controller is highly sensitive are tuned. It is formulated as a nonlinear filtering problem such that both the estimated state and the unknown parameters can be obtained by an extended Kahman filter. The capability of this design method is experimentally demonstrated by applying it to the rejection of a disturbance in a simply supported plate. The other problem considered is that the location where the disturbance enters the system is unknown. This corresponds to an unknown disturbance influence matrix. Under the assumption that the system matrix is known and the disturbance can be measured, it is formulated as a linear filtering problem with an approximate discrete-time design model. Similarly, the estimated state for feedback and the unknown parameters are identified simultaneously and recursively. Also, the feedback gains are calculated approximately by recursively solving the discrete-time control Riccati equation. The effectiveness of the controller is shown by applying it to a simply-supported plate, when the location of the disturbance is assumed unknown. Since implementing LQG self-tuning controllers for vibration control systems requires significant real-time computation, methods that can reduce the computing load are examined. In addition, the possibility of extending the self tuning to disturbance model parameters is explored. / Ph. D.

In this paper the problems of finding error estimates of quadrature formulas are discussed. A method proposed by K.Plukas was tested. One of the most important tests was the one determining the error estimates that are too optimistic. The results have shown that there are 1/8 of such error estimates and that there is no visible pattern when they occur. The second very important test was the one that shows how many iterations are needed to get the estimate of integral. After comparing the results to the ones produced by method of T.O.Espelid it was obvious that method of K.Plukas produced results even when method of T.O.Espelid was not able to. Comparison of these results have also shown that method of K.Plukas is not always as effective as method of T.O.Coteda, i.e. in many cases method of K.Plukas produced the result after more iterations than method of T.O.Coteda.

L’enrichissement des éléments finis standard est un outil performant pour améliorer la qualité d’approximation. L’idée principale de cette approche est d’ajouter aux fonctions de base un ensemble de fonctions censées améliorer la qualité des solutions approchées. Le choix de ces dernières est crucial et est en grande partie basé sur la connaissance a priori de quelques informations telles que les caractéristiques de la solution, de la géométrie du problème à résoudre, etc. L’efficacité de cette approche pour résoudre une équation aux dérivées partielles dans un maillage fixe, sans avoir recours au raffinement, a été prouvée dans de nombreuses applications dans la littérature. La clé de son succès repose principalement sur le bon choix des fonctions de base et plus particulièrement celui des fonctions d’enrichissement. Une question importante se pose alors : quelles conditions faut-il imposer sur les fonctions d’enrichissement afin qu’elles génèrent des éléments finis bien définis ?Dans cette thèse sont abordés différents aspects d’une approche générale d’enrichissement d’éléments finis. Notre première contribution porte principalement sur l’enrichissement de l’élément fini du type Q_1. Par contre, notre seconde contribution, certainement la plus importante, met l’accent sur une approche plus générale pour enrichir n’importe quel élément fini qu’il soit P_k, Q_k ou autres, conformes ou non conformes. Cette approche a conduit à l’obtention des versions enrichies de l’élément de Han, l’élément de Rannacher-Turek et l’élément de Wilson, qui font maintenant partie des codes d’éléments finis les plus couramment utilisés en milieu industriel. Pour établir ces extensions, nous avons eu recours à l’élaboration de nouvelles formules de quadrature multidimensionnelles appropriées généralisant les formules classiques bien connues en dimension 1, dites du “point milieu,” des “trapèzes” et de leurs versions perturbées, ainsi que la formule de Simpson. Elles peuvent être vues comme des extensions naturelles de ces formules en dimension supérieure. Ces dernières, en plus de leurs tests numériques implémentés sous MATLAB, version R2016a, ont fait l’objet de notre troisième contribution. Nous mettons particulièrement l’accent sur la détermination explicite des meilleures constantes possibles apparaissant dans les estimations d’erreur pour ces formules d’intégration. Enfin, dans la quatrième contribution nous testons notre approche pour résoudre numériquement le problème d’élasticité linéaire à l’aide d’un maillage rectangulaire. Nous effectuons l’analyse numérique aussi bien l’analyse de l’erreur d’approximation et résultats de convergence que l’analyse de l’erreur de consistance. Nous montrons également comment cette dernière peut être établie à n’importe quel ordre, généralisant ainsi certains travaux menés dans le domaine. Nous réalisons la mise en œuvre de la méthode et donnons quelques résultats numériques établis à l’aide de la bibliothèque libre d’éléments finis GetFEM++, version 5.0. Le but principal de cette partie sert aussi bien à la validation de nos résultats théoriques, qu’à montrer comment notre approche permet d’élargir la gamme de choix des fonctions d’enrichissement. En outre, elle permet de montrer comment cette large gamme de choix peut aider à avoir des solutions optimales et également à améliorer la validité et la qualité de l’espace d’approximation enrichie. / The enrichment of standard finite elements is a powerful tool to improve the quality of approximation. The main idea of this approach is to incorporate some additional functions on the set of basis functions. These latter are requested to improve the accuracy of the approximate solution. Their best choice is crucial and is based on the knowledge of some a priori information, such as the characteristics of the solution, the geometry of the problem to be solved, etc. The efficiency of such an approach for finding numerical solutions of partial differential equations using a fixed mesh, without recourse to refinement, was proved in numerous applications in the literature. However, the key to its success lies mainly on the best choice of the basis functions, and more particularly those of enrichment functions.An important question then arises: How to suitably choose them, in such a way that they generate a well-defined finite element ?In this thesis, we present a general approach that enables an enrichment of the finite element approximation. This was the subject of our first contribution, which was devoted to the enrichment of the classical Q_1 element, as a first step. As a second step, in our second contribution, we have developed a more general framework for enriching any finite element either P_k, Q_k or others, conforming or nonconforming. As an illustration of how to use this framework to build new enriched finite elements, we have introduced the extensions of some well-known nonconforming finite elements, notably, Han element, Rannacher-Turek element and Wilson element, which are now part of the main code of finite element methods. To establish these extensions, we have introduced a new family of multivariate versions of the classical trapezoidal, midpoint and Simpson rules. These latter, in addition to their numerical tests under MATLAB, version R2016a, have been the subject of our third contribution. They may be viewed as an extension of the well-known trapezoidal, midpoint and Simpson’s one-dimensional rules to higher dimensions. We particularly pay attention to the explicit expressions of the best possible constants appearing in the error estimates for these cubatute formulas. Finally, in the fourth contribution we apply our approach to numerically solving the linear elasticity problem based on a rectangular mesh. We carry out the numerical analysis of the approximation error and also for the consistency error, and show how the latter can be established to any order. This constitutes a generalization of some work already done in the field. In addition to our theoretical results, we have also made some numerical tests, which were achieved by using the GetFEM++ library, version 5.0. The aim of this contribution was not only to confirm our theoretical predictions, but also to show how the new developed framework allows us to expand the range of choices of enrichment functions. Furthermore, we have shown how this wide choices range can help us to improve some approximation properties and to get the optimal solutions for the particular problem of elasticity.

Le sujet de ce travail de thèse est l’application de la méthode de caractéristiques longues (MOC) pour résoudre l’équation du transport des neutrons pour des géométries à trois dimensions extrudées. Les avantages du MOC sont sa précision et son adaptabilité, le point faible était la quantité de ressources de calcul requises. Ce problème est même plus important pour des géométries à trois dimensions ou le nombre d’inconnues du problème est de l’ordre de la centaine de millions pour des calculs d’assemblage.La première partie de la recherche a été dédiée au développement des techniques optimisées pour le traçage et la reconstruction à-la-volé des trajectoires. Ces méthodes profitent des régularités des géométries extrudées et ont permis une forte réduction de l’empreinte mémoire et une réduction des temps de calcul. La convergence du schéma itératif a été accélérée par un opérateur de transport dégradé (DPN) qui est utilisé pour initialiser les inconnues de l’algorithme itératif and pour la solution du problème synthétique au cours des itérations MOC. Les algorithmes pour la construction et la solution des opérateurs MOC et DPN ont été accélérés en utilisant des méthodes de parallélisation à mémoire partagée qui sont le plus adaptés pour des machines de bureau et pour des clusters de calcul. Une partie importante de cette recherche a été dédiée à l’implémentation des méthodes d’équilibrage la charge pour améliorer l’efficacité du parallélisme. La convergence des formules de quadrature pour des cas 3D extrudé a aussi été explorée. Certaines formules profitent de couts négligeables du traitement des directions azimutales et de la direction verticale pour accélérer l’algorithme. La validation de l’algorithme du MOC a été faite par des comparaisons avec une solution de référence calculée par un solveur Monte Carlo avec traitement continu de l’énergie. Pour cette comparaison on propose un couplage entre le MOC et la méthode des Sous-Groupes pour prendre en compte les effets des résonances des sections efficaces. Le calcul complet d’un assemblage de réacteur rapide avec interface fertile/fissile nécessite 2 heures d’exécution avec des erreurs de quelque pcm par rapport à la solution de référence.On propose aussi une approximation d’ordre supérieur du MOC basée sur une expansion axiale polynomiale du flux dans chaque maille. Cette méthode permet une réduction du nombre de mailles (et d’inconnues) tout en gardant la même précision.Toutes les méthodes développées dans ce travail de thèse ont été implémentées dans la version APOLLO3 du solveur de transport TDT. / The topic of our research is the application of the Method of Long Characteristics (MOC) to solve the Neutron Transport Equation in three-dimensional axial geometries. The strength of the MOC is in its precision and versatility. As a drawback, it requires a large amount of computational resources. This problem is even more severe in three-dimensional geometries, for which unknowns reach the order of tens of billions for assembly-level calculations.The first part of the research has dealt with the development of optimized tracking and reconstruction techniques which take advantage of the regularities of three-dimensional axial geometries. These methods have allowed a strong reduction of the memory requirements and a reduction of the execution time of the MOC calculation.The convergence of the iterative scheme has been accelerated with a lower-order transport operator (DPN) which is used for the initialization of the solution and for solving the synthetic problem during MOC iterations.The algorithms for the construction and solution of the MOC and DPN operators have been accelerated by using shared-memory parallel paradigms which are more suitable for standard desktop working stations. An important part of this research has been devoted to the implementation of scheduling techniques to improve the parallel efficiency.The convergence of the angular quadrature formula for three-dimensional cases is also studied. Some of these formulas take advantage of the reduced computational costs of the treatment of planar directions and the vertical direction to speed up the algorithm.The verification of the MOC solver has been done by comparing results with continuous-in-energy Monte Carlo calculations. For this purpose a coupling of the 3D MOC solver with the Subgroup method is proposed to take into account the effects of cross sections resonances. The full calculation of a FBR assembly requires about 2 hours of execution time with differences of few PCM with respect to the reference results.We also propose a higher order scheme of the MOC solver based on an axial polynomial expansion of the unknown within each mesh. This method allows the reduction of the meshes (and unknowns) by keeping the same precision.All the methods developed in this thesis have been implemented in the APOLLO3 version of the neutron transport solver TDT.