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In the first part of this work we generalize a method of building optimal confidence bounds provided in Buehler (1957) by specializing an exhaustive class of confidence regions inspired by Sterne (1954). The resulting confidence regions, also called Buehlerizations, are valid in general models and depend on a designated statistic'' that can be chosen according to some desired monotonicity behaviour of the confidence region. For a fixed designated statistic, the thus obtained family of confidence regions indexed by their confidence level is nested. Buehlerizations have furthermore the optimality property of being the smallest (w.r.t. set inclusion) confidence regions that are increasing in their designated statistic. The theory is eventually applied to normal, binomial, and exponential samples. The second part deals with the statistical comparison of pairs of diagnostic tests and establishes relations 1. between the sets of lower confidence bounds, 2. between the sets of pairs of comparable lower confidence bounds, and 3. between the sets of admissible lower confidence bounds in various models for diverse parameters of interest.
In recent years, the study of dynamical systems has developed into a central research area in mathematics. Actually, in combination with keywords such as "chaos" or "butterfly effect", parts of this theory have been incorporated in other scientific fields, e.g. in physics, biology, meteorology and economics. In general, a discrete dynamical system is given by a set X and a self-map f of X. The set X can be interpreted as the state space of the system and the function f describes the temporal development of the system. If the system is in state x ∈ X at time zero, its state at time n ∈ N is denoted by f^n(x), where f^n stands for the n-th iterate of the map f. Typically, one is interested in the long-time behaviour of the dynamical system, i.e. in the behaviour of the sequence (f^n(x)) for an arbitrary initial state x ∈ X as the time n increases. On the one hand, it is possible that there exist certain states x ∈ X such that the system behaves stably, which means that f^n(x) approaches a state of equilibrium for n→∞. On the other hand, it might be the case that the system runs unstably for some initial states x ∈ X so that the sequence (f^n(x)) somehow shows chaotic behaviour. In case of a non-linear entire function f, the complex plane always decomposes into two disjoint parts, the Fatou set F_f of f and the Julia set J_f of f. These two sets are defined in such a way that the sequence of iterates (f^n) behaves quite "wildly" or "chaotically" on J_f whereas, on the other hand, the behaviour of (f^n) on F_f is rather "nice" and well-understood. However, this nice behaviour of the iterates on the Fatou set can "change dramatically" if we compose the iterates from the left with just one other suitable holomorphic function, i.e. if we consider sequences of the form (g∘f^n) on D, where D is an open subset of F_f with f(D)⊂ D and g is holomorphic on D. The general aim of this work is to study the long-time behaviour of such modified sequences. In particular, we will prove the existence of holomorphic functions g on D having the property that the behaviour of the sequence of compositions (g∘f^n) on the set D becomes quite similarly chaotic as the behaviour of the sequence (f^n) on the Julia set of f. With this approach, we immerse ourselves into the theory of universal families and hypercyclic operators, which itself has developed into an own branch of research. In general, for topological spaces X, Y and a family {T_i: i ∈ I} of continuous functions T_i:X→Y, an element x ∈ X is called universal for the family {T_i: i ∈ I} if the set {T_i(x): i ∈ I} is dense in Y. In case that X is a topological vector space and T is a continuous linear operator on X, a vector x ∈ X is called hypercyclic for T if it is universal for the family {T^n: n ∈ N}. Thus, roughly speaking, universality and hypercyclicity can be described via the following two aspects: There exists a single object which allows us, via simple analytical operations, to approximate every element of a whole class of objects. In the above situation, i.e. for a non-linear entire function f and an open subset D of F_f with f(D)⊂ D, we endow the space H(D) of holomorphic functions on D with the topology of locally uniform convergence and we consider the map C_f:H(D)→H(D), C_f(g):=g∘f|_D, which is called the composition operator with symbol f. The transform C_f is a continuous linear operator on the Fréchet space H(D). In order to show that the above-mentioned "nice" behaviour of the sequence of iterates (f^n) on the set D ⊂ F_f can "change dramatically" if we compose the iterates from the left with another suitable holomorphic function, our aim consists in finding functions g ∈ H(D) which are hypercyclic for C_f. Indeed, for each hypercyclic function g for C_f, the set of compositions {g∘f^n|_D: n ∈ N} is dense in H(D) so that the sequence of compositions (g∘f^n|_D) is kind of "maximally divergent" " meaning that each function in H(D) can be approximated locally uniformly on D via subsequences of (g∘f^n|_D). This kind of behaviour stands in sharp contrast to the fact that the sequence of iterates (f^n) itself converges, behaves like a rotation or shows some "wandering behaviour" on each component of F_f. To put it in a nutshell, this work combines the theory of non-linear complex dynamics in the complex plane with the theory of dynamics of continuous linear operators on spaces of holomorphic functions. As far as the author knows, this approach has not been investigated before.
Die vorliegende Arbeit teilt sich in die zwei titelgebenden Themengebiete. Inhalt des ersten Teils dieser Arbeit ist die Untersuchung der Proximität, also einer gewissen Messung der Nähe, von Binomial- und Poisson-Verteilungen. Speziell wird die uniforme Struktur des Totalvariationsabstandes auf der abgeschlossenen Menge aller Binomial- und Poisson-Verteilungen charakterisiert, und zwar mit Hilfe der die Verteilungen eindeutig bestimmenden zugehörigen Erwartungswerte und Varianzen. Insbesondere wird eine obere Abschätzung des Totalvariationsabstandes auf der Menge der Binomial- und Poisson-Verteilungen durch eine entsprechende Funktion der zugehörigen Erwartungswerte und Varianzen angegeben. Der zweite Teil der Arbeit widmet sich Konfidenzintervallen für Durchschnitte von Erfolgswahrscheinlichkeiten. Eine der ersten und bekanntesten Arbeiten zu Konfidenzintervallen von Erfolgswahrscheinlichkeiten ist die von Clopper und Pearson (1934). Im Binomialmodell werden hier bei bekanntem Stichprobenumfang und Konfidenzniveau Konfidenzintervalle für die unbekannte Erfolgswahrscheinlichkeit entwickelt. Betrachtet man bei festem Stichprobenumfang statt einer Binomialverteilung, also dem Bildmaß einer homogenen Bernoulli-Kette unter der Summationsabbildung, das entsprechende Bildmaß einer inhomogenen Bernoulli-Kette, so erhält man eine Bernoulli-Faltung mit den entsprechenden Erfolgswahrscheinlichkeiten. Für das Schätzen der durchschnittlichen Erfolgswahrscheinlichkeit im größeren Bernoulli-Faltungs-Modell sind z. B. die einseitigen Clopper-Pearson-Intervalle im Allgemeinen nicht gültig. Es werden hier optimale einseitige und gültige zweiseitige Konfidenzintervalle für die durchschnittliche Erfolgswahrscheinlichkeit im Bernoulli-Faltungs-Modell entwickelt. Die einseitigen Clopper-Pearson-Intervalle sind im Allgemeinen auch nicht gültig für das Schätzen der Erfolgswahrscheinlichkeit im hypergeometrischen Modell, das ein Teilmodell des Bernoulli-Faltungs-Modells ist. Für das hypergeometrische Modell mit festem Stichprobenumfang und bekannter Urnengröße sind die optimalen einseitigen Konfidenzintervalle bekannt. Bei festem Stichprobenumfang und unbekannter Urnengröße werden aus den im Bernoulli-Faltungs-Modell optimalen Konfidenzintervallen optimale Konfidenzintervalle für das hypergeometrische Modell entwickelt. Außerdem wird der Fall betrachtet, dass eine obere Schranke für die unbekannte Urnengröße gegeben ist.
Zu den klassischen Verteilungen der mathematischen Statistik zählen die zentralen F- und t-Verteilungen. Die vorliegende Arbeit untersucht Verallgemeinerungen dieser Verteilungen, die sogenannten doppelt nichtzentralen F- und t-Verteilungen, welche in der statistischen Testtheorie von Bedeutung sind. Die Tatsache, dass die zugehörigen Wahrscheinlichkeitsdichten nur in Form von Parameterintegral- bzw. Doppelreihendarstellungen gegeben sind, stellt eine große Herausforderung bei der Untersuchung analytischer Eigenschaften dar. Unter Verwendung von Techniken aus der Theorie der vorzeichenregulären Funktionen gelingt es, die bisher vermutete, jedoch lediglich aus Approximationen abgeleitete, strikt unimodale Gestalt der Dichtefunktion für eine große Klasse doppelt nichtzentraler Verteilungen zu zeigen. Dieses Resultat gestattet die Untersuchung des eindeutig bestimmten Modus als Funktion gewisser Nichtzentralitätsparameter. Hier erweist sich die Theorie der vorzeichenregulären Funktionen als wichtiges Hilfsmittel, um monotone Abhängigkeiten nachzuweisen.
In a paper of 1996 the british mathematician Graham R. Allan posed the question, whether the product of two stable elements is again stable. Here stability describes the solvability of a certain infinite system of equations. Using a method from the theory of homological algebra, it is proved that in the case of topological algebras with multiplicative webs, and thus in all common locally convex topological algebras that occur in standard analysis, the answer of Allan's question is affirmative.
In splitting theory of locally convex spaces we investigate evaluable characterizations of the pairs (E, X) of locally convex spaces such that each exact sequence 0 -> X -> G -> E -> 0 of locally convex spaces splits, i.e. either X -> G has a continuous linear left inverse or G -> E has a continuous linear right inverse. In the thesis at hand we deal with splitting of short exact sequences of so-called PLH spaces, which are defined as projective limits of strongly reduced spectra of strong duals of Fréchet-Hilbert spaces. This class of locally convex spaces contains most of the spaces of interest for application in the theory of partial differential operators as the space of Schwartz distributions , the space of real analytic functions and various spaces of ultradifferentiable functions and ultradistributions. It also contains non-Schwartz spaces as B(2,k,loc)(Ω) and spaces of smooth and square integrable functions that are not covered by the current theory for PLS spaces. We prove a complete characterizations of the above problem in the case of X being a PLH space and E either being a Fréchet-Hilbert space or a strong dual of one by conditions of type (T ). To this end, we establish the full homological toolbox of Yoneda Ext functors in exact categories for the category of PLH spaces including the long exact sequence, which in particular involves a thorough discussion of the proper concept of exactness. Furthermore, we exhibit the connection to the parameter dependence problem via the Hilbert tensor product for hilbertizable locally convex spaces. We show that the Hilbert tensor product of two PLH spaces is again a PLH space which in particular proves the positive answer to Grothendieck- problème des topologies. In addition to that we give a complete characterization of the vanishing of the first derivative of the functor proj for tensorized PLH spectra if one of the PLH spaces E and X meets some nuclearity assumptions. To apply our results to concrete cases we establish sufficient conditions of (DN)-(Ω) type and apply them to the parameter dependence problem for partial differential operators with constant coefficients on B(2,k,loc)(Ω) spaces as well as to the smooth and square integrable parameter dependence problem. Concluding we give a complete solution of all the problems under consideration for PLH spaces of Köthe type.
In dieser Dissertation beschäftigen wir uns mit der konstruktiven und generischen Gewinnung universeller Funktionen. Unter einer universellen Funktion verstehen wie dabei eine solche holomorphe Funktion, die in gewissem Sinne ganze Klassen von Funktionen enthält. Die konstruktive Methode beinhaltet die explizite Konstruktion einer universellen Funktion über einen Grenzprozess, etwa als Polynomreihe. Die generische Methode definiert zunächst rein abstrakt die jeweils gewünschte Klasse von universellen Funktionen. Mithilfe des Baireschen Dichtesatzes wird dann gezeigt, dass die Klasse dieser Funktionen nicht nur nichtleer, sondern sogar G_delta und dicht in dem betrachteten Funktionenraum ist. Beide Methoden bedienen sich der Approximationssätze von Runge und von Mergelyan. Die Hauptergebnisse sind die folgenden: (1) Wir haben konstruktiv die Existenz von universellen Laurentreihen auf mehrfach zusammenhängenden Gebieten bewiesen. Zusätzlich haben wir gezeigt, dass die Menge solcher universeller Laurentreihen dicht im Raum der auf dem betrachteten Gebiet holomorphen Funktionen ist. (2) Die Existenz von universellen Faberreihen auf gewissen Gebieten wurde sowohl konstruktiv als auch generisch bewiesen. (3) Zum einen haben wir konstruktiv gezeigt, dass es so genannte ganze T-universelle Funktionen mit vorgegebenen Approximationswegen gibt. Die Approximationswege sind durch eine hinreichend variable funktionale Form vorgegeben. Die Menge solcher Funktionen ist im Raum der ganzen Funktionen eine dichte G_delta-Menge. Zum anderen haben wir generisch die Existenz von auf einem beschränkten Gebiet T-universellen Funktionen bezüglich gewisser vorgegebener Approximationswege bewiesen. Die Approximationswege sind auch hier genügend allgemein.
This work investigates the industrial applicability of graphics and stream processors in the field of fluid simulations. For this purpose, an explicit Runge-Kutta discontinuous Galerkin method in arbitrarily high order is implemented completely for the hardware architecture of GPUs. The same functionality is simultaneously realized for CPUs and compared to GPUs. Explicit time steppings as well as established implicit methods are under consideration for the CPU. This work aims at the simulation of inviscid, transsonic flows over the ONERA M6 wing. The discontinuities which typically arise in hyperbolic equations are treated with an artificial viscosity approach. It is further investigated how this approach fits into the explicit time stepping and works together with the special architecture of the GPU. Since the treatment of artificial viscosity is close to the simulation of the Navier-Stokes equations, it is reviewed how GPU-accelerated methods could be applied for computing viscous flows. This work is based on a nodal discontinuous Galerkin approach for linear hyperbolic problems. Here, it is extended to non-linear problems, which makes the application of numerical quadrature obligatory. Moreover, the representation of complex geometries is realized using isoparametric mappings. Higher order methods are typically very sensitive with respect to boundaries which are not properly resolved. For this purpose, an approach is presented which fits straight-sided DG meshes to curved geometries which are described by NURBS surfaces. The mesh is modeled as an elastic body and deformed according to the solution of closest point problems in order to minimize the gap to the original spline surface. The sensitivity with respect to geometry representations is reviewed in the end of this work in the context of shape optimization. Here, the aerodynamic drag of the ONERA M6 wing is minimized according to the shape gradient which is implicitly smoothed within the mesh deformation approach. In this context a comparison to the classical Laplace-Beltrami operator is made in a Stokes flow situation.
The Hadamard product of two holomorphic functions which is defined via a convolution integral constitutes a generalization of the Hadamard product of two power series which is obtained by pointwise multiplying their coefficients. Based on the integral representation mentioned above, an associative law for this convolution is shown. The main purpose of this thesis is the examination of the linear and continuous Hadamard convolution operators. These operators map between spaces of holomorphic functions and send - with a fixed function phi - a function f to the convolution of phi and f. The transposed operator is computed and turns out to be a Hadamard convolution operator, too, mapping between spaces of germs of holomorphic functions. The kernel of Hadamard convolution operators is investigated and necessary and sufficient conditions for those operators to be injective or to have dense range are given. In case that the domain of holomorphy of the function phi allows a Mellin transform of phi, certain (generalized) monomials are identified as eigenfunctions of the corresponding operator. By means of this result and some extract of the theory of growth of entire functions, further propositions concerning the injectivity, the denseness of the range or the surjectivity of Hadamard convolution operators are shown. The relationship between Hadamard convolution operators, operators which are defined via the convolution with an analytic functional and differential operators of infinite order is investigated and the results which are obtained in the thesis are put into the research context. The thesis ends with an application of the results to the approximation of holomorphic functions by lacunary polynomials. On the one hand, the question under which conditions lacunary polynomials are dense in the space of all holomorphic functions is investigated and on the other hand, the rate of approximation is considered. In this context, a result corresponding to the Bernstein-Walsh theorem is formulated.
Copositive programming is concerned with the problem of optimizing a linear function over the copositive cone, or its dual, the completely positive cone. It is an active field of research and has received a growing amount of attention in recent years. This is because many combinatorial as well as quadratic problems can be formulated as copositive optimization problems. The complexity of these problems is then moved entirely to the cone constraint, showing that general copositive programs are hard to solve. A better understanding of the copositive and the completely positive cone can therefore help in solving (certain classes of) quadratic problems. In this thesis, several aspects of copositive programming are considered. We start by studying the problem of computing the projection of a given matrix onto the copositive and the completely positive cone. These projections can be used to compute factorizations of completely positive matrices. As a second application, we use them to construct cutting planes to separate a matrix from the completely positive cone. Besides the cuts based on copositive projections, we will study another approach to separate a triangle-free doubly nonnegative matrix from the completely positive cone. A special focus is on copositive and completely positive programs that arise as reformulations of quadratic optimization problems. Among those we start by studying the standard quadratic optimization problem. We will show that for several classes of objective functions, the relaxation resulting from replacing the copositive or the completely positive cone in the conic reformulation by a tractable cone is exact. Based on these results, we develop two algorithms for solving standard quadratic optimization problems and discuss numerical results. The methods presented cannot immediately be adapted to general quadratic optimization problems. This is illustrated with examples.