Dissertations / Theses on the topic 'Directional derivatives'

Wir befassen uns mit Gleichgewichtsproblemen, die bei dem Zusammentreffen von Märkten und Marktteilnehmern entstehen, zuerst in einem Modell mit konkurrierenden Märkten mit Feedback und asymmetrischer Information und dann mit strategisch interagierenden Händlern. Zudem untersuchen wir spezielle Richtungsableitung im Kontext des pfadweisen Malliavinkalküls. Im ersten Kapitel analysieren wir ein Prinzipal-Agenten-Problem mit einem monopolistischen Dealer, der mit einem Crossing-Netzwerk (CN) um den Handel mit Agenten mit privater Information konkurriert. Wir untersuchen die gewinnmaximierenden Angebote des Dealers für unterschiedliche Outside-Optionen und formulieren hinreichende Bedingungen für die Existenz und Eindeutigkeit einer optimalen Lösung. In unserem Modell ist die Einführung des CN für die Agenten vorteilhaft und ein Gleichgewichtspreis existiert. Im zweiten Kapitel analysieren wir den Einfluss vergleichender Leistungsbewertung von Händlern auf die Preisfindung im Marktgleichgewicht. Ein Derivat soll einen markträumenden Preis bekommen unter Beachtung der strategisch handelnden Agenten. Das Risiko eines Händlers setzt sich aus dem eigenen Risikoprofil und dem Erfolg des Handelns relativ zum durchschnittlichen Handelserfolg aller zusammen und er wird durch eine BSDE gemessen. Wir bestimmen einen repräsentativen Agenten und zeigen so die Existenz und Eindeutigkeit eines Gleichgewichtspreises. Weiterhin können wir diesen charakterisieren und im Spezialfall von entropischen Risikomaßen konkret berechnen. In diesem Spezialfall führen wir auch eine Parameteranalyse durch. Das dritte Kapitel verknüpft klassischen und pfadweisen Malliavinkalkül. Wir definieren und analysieren pfadweise Richtungsableitungen mit Hilfe von Perturbationen mit Cameron-Martin-Funktionen, mit (Hölder-)stetigen Funktionen, mit unstetigen Funktionen und mit Maßen. Somit sind sowohl die klassische Malliavin-Ableitung als auch Dupires vertikale Ableitung als Spezialfälle enthalten.
We analyze equilibrium problems arising from interacting markets and market participants, first competing markets with feedback and asymmetric information, then strategically interacting traders; moreover we analyze a new notion of a pathwise directional derivative in the context of pathwise Malliavin calculus. The first chapter analyzes a principal-agent game in which a monopolistic profit-maximizing dealer competes with a crossing network (CN) for trading with privately informed agents. We analyze the structure of the dealer’s offered pricing schedules for different outside options. We give sufficient conditions for the existence and uniqueness of a solution to the dealer’s problem and show that in our setting the introduction of the CN is beneficial for the agents. Additionally, we discuss existence and uniqueness of an equilibrium price for the feedback between dealer and CN. In the second chapter we analyze the impact of performance concerns on a problem of equilibrium pricing. A derivative is priced such that the market clears, given strategically behaving agents. Their risk stems from a risky position in the future and the relative trading gains compared to all other agents. The risk measure of each agent is specified by a BSDE. In spite of the strategic interaction, we are able to apply a representative agent approach to obtain existence and uniqueness of the equilibrium market price of external risk. In the special case of entropic risk measures, we perform a parameter analysis. The third chapter provides a link between classical and pathwise Malliavin calculus. We define and analyze pathwise directional derivatives via perturbations with Cameron-Martin functions, (Hölder-)continuous functions, discontinuous functions and measures, thereby including both the traditional Malliavin derivative and the vertical derivative from Dupire’s work.

Thesis (Ph.D.)--University of Missouri-Columbia, 2006.
The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (March 1, 2007) Vita. Includes bibliographical references.

Dans un grand nombre de domaines, l'analyse modale de structures est une composante capitale du dimensionnement. Pour l'identification des fréquences et modes propres, les logiciels de calcul éléments finis sont maintenant souvent utilisés et offrent des réponses rapides et satisfaisantes dans une grande majorité de cas. Cependant, lorsqu'une structure possède une géométrie qui varie au cours du temps ou alors lorsqu'une fissure se propage dans cette structure, les méthodes classiques employées peuvent être contraignantes et consommatrice de temps CPU (remaillage, résolution itérative de problèmes aux valeurs propres...), surtout si l'on veut suivre l'évolution des solutions propres.Dans ces travaux de doctorat, une méthode originale est proposée afin d’améliorer la gestion de l’analyse modale de structures subissant des changements de forme au cours du temps. Celle-ci est basée sur les dérivées directionnelles et sur la méthode X-FEM. En effet, les dérivées directionnelles permettent de prédire l’évolution des solutions propres entre deux configurations temporelles de la structure et X-FEM permet de s’affranchir des contraintes liées au maillage de chacune des configurations. Grâce à des critères spécifiquement développés, la méthodologie a été testée pour des cas de problèmes plans et axysymétrique. Les résultats obtenus en regard des méthodes classiques et les conclusions qu’elles peuvent amener, permettent de voir les nombreux avantages de l’outil que nous avons proposé
In many industrial fields, modal analysis of structures is a primary key during the design. Finite Element Method is often used to identify both natural frequencies and shapes, offering quick and satisfactory answers in most cases. However, when a structure possesses a time-dependent geometry or if the structure is subjected to a crack propagation, the standards methods used can be constraining. They can also be CPU time consuming (due to remeshing, iterative solving of eigenvalue problems…), especially if one wants to track the evolution of the eigensolutions.In this research work, an original method is proposed to improve the management of finding the evolution of eigensolutions in case of time-dependent structures. This methology is based on the combination of directional derivatives and X-FEM. The directional derivatives allow to estimate the evolution of the eigensolutions between two configurations of the structure and X-FEM overcomes the constraints related to mesh generation of each configuration. Through specific developed criteria, the methodology has been tested for cases of plane and axisymmetric problems. The results obtained in comparison to the standard modal analyses and the conclusions that they can bring, highlight the advantages of the numerical tool that we proposed

The geometrically nonlinear constant moment triangle based on the von Karman theory of thin plates is first described. This finite element, which is believed to be the simplest possible element to pass the totality of the von Karman patch test, is employed throughout the present work. It possesses the special characteristic of providing a tangent stiffness matrix which is accurate and without approximation. The stability of equilibrium of discrete conservative systems is discussed. The criteria which identify the critical points (limit and bifurcation), and the method of determination of the stability coefficients are presented in a simple matrix formulation which is suitable for computation. An alternative formulation which makes direct use of higher order directional derivatives of the total potential energy is also presented. Continuation along the stable equilibrium solution path is achieved by using a recently developed Newton method specially modified so that stable points are points of attraction. In conjunction with this solution technique, a branch switching method is introduced which directly computes any intersecting branches. Bifurcational buckling often exhibits huge structural changes and it is believed that the computation of the required switch procedure is performed here, and for the first time, in a satisfactory manner. Hence, both limit and bifurcation points can be treated without difficulty and with continuation into the post buckling regime. In this way, the ability to compute the stable equilibrium path throughout the load-deformation history is accomplished. Two numerical examples which exhibit bifurcational buckling are treated in detail and provide numerical evidence as to the ability of the employed techniques to handle even the most complex problems. Although only relatively coarse finite element meshes are used it is evident that the technique provides a powerful tool for any kind of thin elastic plate and shell problem. The thesis concludes with a proposal for an algorithm to automate the computation of the unknown parameter in the branch switching method.

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CNPq
Neste trabalho estudamos a existência de, pelo menos, três soluções distintas para dois problemas de inclusão diferencial. Para isto, faremos uso da teoria da análise convexa para funcionais localmente Lipschitz, bem como métodos variacionais.
In this work we study the existence of, at least, three distinct solutions to two problems of differential inclusion. For this, we use the theory of convex functional analysis Lipschitz locally, and variational methods.

U disertaciji su posmatrani projektivni postupci tipa konjugovanih gradijenata za rešavanje nelinearnih monotonih sistema velikih dimenzija. Ovi postupci kombinuju projektivnu metodu sa pravcima pretraživanja tipa konjugovanih gradijenata. Zbog osobine monotonosti sistema, projektivna metoda omogućava jednostavnu globalizaciju, a pravci pretraživanja tipa konjugovanih gradijenata zahtevaju maloračunarske memorije pa su pogodni za rešavanje sistema velikih dimenzija. Projektivni postupci tipa konjugovanih gradijenata ne koriste izvode niti funkciju cilja i zasnovani su samo na izračunavanju vrednosti funkcije sistema, pa su pogodni i za rešavanje neglatkih monotonih sistema. Pošto se globalna konvergencija dokazuje bez pretpostavki o regularnosti, ovi postupci se mogu koristiti i za rešavanje sistema sa singularnim rešenjima. U disertaciji su definisana tri nova tročlana pravca pretraživanjatipa Flečer-Rivs i dva nova hibridna pravca tipa Hu-Stori. Formulisani su projektivni postupci sa novim pravcima pretraživanja i dokazana je njihova globalna konvergencija. Numeričke performanse postupaka testirane su na relevantnim primerima i poređene sa poznatim postupcima iz literature. Numerički rezultati potvrđuju da su novi postupci robusni, efikasni i uporedivi sa postojećim postupcima.
Projection based CG methods for solving large-scale nonlinear monotone systems are considered in this thesis. These methods combine hyperplane projection technique with conjugate gradient (CG) search directions. Hyperplane projection method is suitable for monotone systems, because it enables simply globalization, while CG directions are efficient for large-scale nonlinear systems, due to low memory. Projection based CG methods are funcion-value based, they don’t use merit function and derivatives, and because of that they are also suitable for solving nonsmooth monotone systems. The global convergence of these methods are ensured without additional regularity assumptions, so they can be used for solving singular systems.Three new three-term search directions of Fletcher-Reeves type and two new hybrid search directions of Hu-Storey type are defined. PCG algorithm with five new CG type directions is proposed and its global convergence is established. Numerical performances of methods are tested on relevant examples from literature. These results point out that new projection based CG methods have good computational performances. They are efficient, robust and competitive with other methods.

Dans cette thèse, nous étudions le problème de réduction de la dimension dans le cadre du modèle de régression suivant Y=g(B X,e), où X est un vecteur de dimension p, Y appartient à R, la fonction g est inconnue et le bruit e est indépendant de X. Nous nous intéressons à l'estimation de la matrice B, de taille dxp où d est plus petit que p, (dont la connaissance permet d'obtenir de bonnes vitesses de convergence pour l'estimation de g). Ce problème est traité en utilisant deux approches distinctes. La première, appelée régression inverse nécessite la condition de linéarité sur X. La seconde, appelée semi-paramétrique ne requiert pas une telle condition mais seulement que X possède une densité lisse. Dans le cadre de la régression inverse, nous étudions deux familles de méthodes respectivement basées sur E[X f(Y)] et E[XX^T f(Y)]. Pour chacune de ces familles, nous obtenons les conditions sur f permettant une estimation exhaustive de B, aussi nous calculons la fonction f optimale par minimisation de la variance asymptotique. Dans le cadre de l'approche semi-paramétrique, nous proposons une méthode permettant l'estimation du gradient de la fonction de régression. Sous des hypothèses semi-paramétriques classiques, nous montrons la normalité asymptotique de notre estimateur et l'exhaustivité de l'estimation de B. Quel que soit l'approche considérée, une question fondamentale est soulevée : comment choisir la dimension de B ? Pour cela, nous proposons une méthode d'estimation du rang d'une matrice par test d'hypothèse bootstrap.

This thesis develops methodologies for the construction of various types of optimal designs with applications in maximum likelihood estimation and factorial structure design. The methodologies are applied to some real data sets throughout the thesis. We start with a broad review of optimal design theory including various types of optimal designs along with some fundamental concepts. We then consider a class of optimization problems and determine the optimality conditions. An important tool is the directional derivative of a criterion function. We study extensively the properties of the directional derivatives. In order to determine the optimal designs, we consider a class of multiplicative algorithms indexed by a function, which satisfies certain conditions. The most important and popular design criterion in applications is D-optimality. We construct such designs for various regression models and develop some useful strategies for better convergence of the algorithms. The remaining thesis is devoted to some important applications of optimal design theory. We first consider the problem of determining maximum likelihood estimates of the cell probabilities under the hypothesis of marginal homogeneity in a square contingency table. We formulate the Lagrangian function and remove the Lagrange parameters by substitution. We then transform the problem to one of maximizing some functions of the cell probabilities simultaneously. We apply this problem to some real data sets, namely, a US Migration data, and a data on grading of unaided distance vision. We solve another estimation problem to determine the maximum likelihood estimation of the parameters of the latent variable models such as Bradley-Terry model where the data come from a paired comparisons experiment. We approach this problem by considering the observed frequency having a binomial distribution and then replacing the binomial parameters in terms of optimal design weights. We apply this problem to a data set from American League Baseball Teams. Finally, we construct some optimal structure designs for comparing test treatments with a control. We introduce different structure designs and establish their properties using the incidence and characteristic matrices. We also develop methods of obtaining optimal R-type structure designs and show how such designs are trace, A- and MV-optimal.
October 2016

Previous papers have elaborated formal gradient analysis for spatial processes, focusing on the distribution theory for directional derivatives associated with a response variable assumed to follow a Gaussian process model. In the current work, these ideas are extended to additionally accommodate one or more continuous covariate(s) whose directional derivatives are of interest and to relate the behavior of the directional derivatives of the response surface to those of the covariate surface(s). It is of interest to assess whether, in some sense, the gradients of the response follow those of the explanatory variable(s), thereby gaining insight into the local relationships between the variables. The joint Gaussian structure of the spatial random effects and associated directional derivatives allows for explicit distribution theory and, hence, kriging across the spatial region using multivariate normal theory. The gradient analysis is illustrated for bivariate and multivariate spatial models, non-Gaussian responses such as presence-absence and point patterns, and outlined for several additional spatial modeling frameworks that commonly arise in the literature. Working within a hierarchical modeling framework, posterior samples enable all gradient analyses to occur as post model fitting procedures.

Dissertation

A dissertation submitted to the Faculty of Science, University of the Witwatersrand, in fulfillment of the requirements for the degree of Master of Science, May 14, 2013.
In this dissertation, we investigate the parabolic mixed derivative diffusion equation modeling the viscous and viscoelastic effects in a non-Newtonian viscoelastic fluid. The model is analytically considered using Fourier and Laplace transformations. The main focus of the dissertation, however, is the implementation of the Peaceman-Rachford Alternating Direction Implicit method. The one-dimensional parabolic mixed derivative diffusion equation is extended to a two-dimensional analog. In order to do this, the two-dimensional analog is solved using a Crank-Nicholson method and implemented according to the Peaceman- Rachford ADI method. The behaviour of the solution of the viscoelastic fluid model is analysed by investigating the effects of inertia and diffusion as well as the viscous behaviour, subject to the viscosity and viscoelasticity parameters. The two-dimensional parabolic diffusion equation is then implemented with a high-order method to unveil more accurate solutions. An error analysis is executed to show the accuracy differences between the numerical solutions of the general ADI and high-order compact methods. Each of the methods implemented in this dissertation are investigated via the von-Neumann stability analysis to prove stability under certain conditions.

This thesis deals with the introduction of function of two variables and differential calculus of this function. This work should serve as a textbook for students of elementary school's teacher. Each chapter contains a summary of basic concepts and explanations of relationships, then solved model exercises of the topic and finally the exercises, which should solve the student himself. Thesis have transmit to students basic knowledges of differential calculus of functions of two variables, including practical knowledges.

This thesis develops efficient modeling frameworks via a Partial Differential Equation (PDE) approach for multi-factor financial derivatives, with emphasis on three-factor models, and studies highly efficient implementations of the numerical methods on novel high-performance computer architectures, with particular focus on Graphics Processing Units (GPUs) and multi-GPU platforms/clusters of GPUs. Two important classes of multi-factor financial instruments are considered: cross-currency/foreign exchange (FX) interest rate derivatives and multi-asset options. For cross-currency interest rate derivatives, the focus of the thesis is on Power Reverse Dual Currency (PRDC) swaps with three of the most popular exotic features, namely Bermudan cancelability, knockout, and FX Target Redemption. The modeling of PRDC swaps using one-factor Gaussian models for the domestic and foreign interest short rates, and a one-factor skew model for the spot FX rate results in a time-dependent parabolic PDE in three space dimensions. Our proposed PDE pricing framework is based on partitioning the pricing problem into several independent pricing subproblems over each time period of the swap's tenor structure, with possible communication at the end of the time period. Each of these subproblems requires a solution of the model PDE. We then develop a highly efficient GPU-based parallelization of the Alternating Direction Implicit (ADI) timestepping methods for solving the model PDE. To further handle the substantially increased computational requirements due to the exotic features, we extend the pricing procedures to multi-GPU platforms/clusters of GPUs to solve each of these independent subproblems on a separate GPU. Numerical results indicate that the proposed GPU-based parallel numerical methods are highly efficient and provide significant increase in performance over CPU-based methods when pricing PRDC swaps. An analysis of the impact of the FX volatility skew on the price of PRDC swaps is provided. In the second part of the thesis, we develop efficient pricing algorithms for multi-asset options under the Black-Scholes-Merton framework, with strong emphasis on multi-asset American options. Our proposed pricing approach is built upon a combination of (i) a discrete penalty approach for the linear complementarity problem arising due to the free boundary and (ii) a GPU-based parallel ADI Approximate Factorization technique for the solution of the linear algebraic system arising from each penalty iteration. A timestep size selector implemented efficiently on GPUs is used to further increase the efficiency of the methods. We demonstrate the efficiency and accuracy of the proposed GPU-based parallel numerical methods by pricing American options written on three assets.

Generalized linear mixture models (GLMM) are widely used in statistical applications to model count and binary data. We consider the problem of nonparametric likelihood estimation of mixing distributions in GLMM's with multiple random effects. The log-likelihood to be maximized has the general form l(G)=Σi log∫f(yi,γ) dG(γ) where f(.,γ) is a parametric family of component densities, yi is the ith observed response dependent variable, and G is a mixing distribution function of the random effects vector γ defined on Ω. The literature presents many algorithms for maximum likelihood estimation (MLE) of G in the univariate random effect case such as the EM algorithm (Laird, 1978), the intra-simplex direction method, ISDM (Lesperance and Kalbfleish, 1992), and vertex exchange method, VEM (Bohning, 1985). In this dissertation, the constrained Newton method (CNM) in Wang (2007), which fits GLMM's with random intercepts only, is extended to fit clustered datasets with multiple random effects. Owing to the general equivalence theorem from the geometry of mixture likelihoods (see Lindsay, 1995), many NPMLE algorithms including CNM and ISDM maximize the directional derivative of the log-likelihood to add potential support points to the mixing distribution G. Our method, Direct Search Directional Derivative (DSDD), uses a directional search method to find local maxima of the multi-dimensional directional derivative function. The DSDD's performance is investigated in GLMM where f is a Bernoulli or Poisson distribution function. The algorithm is also extended to cover GLMM's with zero-inflated data. Goodness-of-fit (GOF) and selection methods for mixed models have been developed in the literature, however their application in models with nonparametric random effects distributions is vague and ad-hoc. Some popular measures such as the Deviance Information Criteria (DIC), conditional Akaike Information Criteria (cAIC) and R2 statistics are potentially useful in this context. Additionally, some cross-validation goodness-of-fit methods popular in Bayesian applications, such as the conditional predictive ordinate (CPO) and numerical posterior predictive checks, can be applied with some minor modifications to suit the non-Bayesian approach.
Graduate
0463
rabihsaab@gmail.com