The Ph.D. Thesis “Strong mixing measures and invariant sets in linear dynamics” has three differenced parts. Chapter 0 introduces the notation, definitions and the basic results that will be needed troughout the thesis. There is a first part consisting of Chapters 1 and 2, where we study the relation between the Frequent Hypercyclicity Criterion and the existence of strongly-mixing Borel probability measures. A third chapter, where we focus our attention on frequent hypercyclicity for translation C0-semigroups, and the last part corresponding to Chapters 4 and 5, where we study dynamical properties satisfied by autonomous and non-autonomous linear dynamical systems on certain invariant sets. In what follows, we give a brief description of each chapter: In Chapter 1, we construct strongly mixing Borel probability T-invariant measures with full support for operators on F-spaces which satisfy the Frequent Hypercyclicity Criterion. Moreover, we provide examples of operators that verify this criterion and we also show that this result can be improved in the case of chaotic unilateral backward shifts. The contents of this chapter have been published in [88] and [12]. In Chapter 2, we show that the Frequent Hypercyclicity Criterion for C0- semigroups, which was given by Mangino and Peris in [82], ensures the existence of invariant strongly mixing measures with full support. We will provide several examples, that range from birth-and-death models to the Black-Scholes equation, which illustrate these results. All the results of this chapter have been published in [86]. In Chapter 3, we focus our attention on one of the most important tests C0-semigroups, the translation semigroup. Inspired in the work of Bayart and Ruzsa in [22], where they characterize frequent hypercyclicity of weighted backward shifts we characterize frequently hypercyclic translation C0-semigroups on C ρ 0 (R) and L ρ p(R). Moreover, we first review some known results on the dynamics of the translation C0-semigroups. Later we state and prove a characterization of frequent hypercyclicity for weighted pseudo shifts in terms of the weights that will be used later to obtain a characterization of frequent hypercyclicity for translation C0-semigroups on C ρ 0 (R). Finally we study the case of L ρ p(R). We will also establish an analogy between the study of frequent hypercyclicity for the translation C0-semigroup in L ρ p(R) and the corresponding one for backward shifts on weighted sequence spaces. The contents of this chapter have been included in [81]. Chapter 4 is devoted to study hypercyclicity, Devaney chaos, topological mixing properties and strong mixing in the measure-theoretic sense for operators on topological vector spaces with invariant sets. More precisely, we establish links between the fact of satisfying any of our dynamical properties on certain invariant sets, and the corresponding property on the closed linear span of the invariant set, or on the union of the invariant sets. Viceversa, we give conditions on the operator (or C0-semigroup) to ensure that, when restricted to the invariant set, it satisfies certain dynamical property. Particular attention is given to the case of positive operators and semigroups on lattices, and the (invariant) positive cone. The contents of this chapter have been published in [85]. In the last chapter, motivated by the work of Balibrea and Oprocha [4], where they obtained several results about weak mixing and chaos for nonautonomous discrete systems on compact sets, we study mixing properties for nonautonomous linear dynamical systems that are induced by the corresponding dynamics on certain invariant sets. All the results of this chapter have been published in [87]. / Murillo Arcila, M. (2015). Strong mixing measures and invariant sets in linear dynamics [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/48519

Title: Long range dependence in time series Author: Alexander Till Department: Department of Probability and Mathematical Statistics Supervisor: RNDr. Michaela Prokešová, Ph.D. Abstract: The diploma thesis demonstrates the necessity of a study of long range dependence, introduces fractional Gaussian noise and discusses possible definitions of long memory. It is done by notions of ergodic theory and by second moment characteristics and spectral density. These definitions are confronted with the model of fractional Gaussian noise and with intuitive understanding of long range memory. Relations and connections between these criteria are studied as well. The work is restricted to the study of discrete time processes. 1

Title: Long range dependence in time series Author: Alexander Till Department: Department of Probability and Mathematical Statistics Supervisor: RNDr. Michaela Prokešová, Ph.D. Abstract: The diploma thesis demonstrates the necessity of a study of long range dependence, introduces fractional Gaussian noise and discusses possi- ble definitions of long memory. It is done by notions of ergodic theory and by second moment characteristics and spectral density. These definitions are confronted with the model of fractional Gaussian noise and with intuitive un- derstanding of long range memory. Relations and connections between these criteria are studied as well. The work is restricted to the study of discrete time processes. Method for Hurst index estimation for fractional Gaussian noise and it's application on logarithmic returns of shares of selected produ- cers of beer are included in this work. 1

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Le thème de cette thèse est la théorie spatiale des valeurs extrêmes, et les objets principalement étudiés sont les processus max-stables à trajectoires continues. Nous commençons par déterminer la convergence des maximums de processus stochastiques indépendants, en utilisant la convergence de mesures empiriques vers des processus ponctuels de Poisson. Ensuite, nous déterminons les lois conditionnelles des processus max infiniment divisibles (max-i.d). La représentation des processus max-i.d par des processus ponctuels de Poisson permet l'introduction de notions telles que les fonctions extrémales et le hitting scénario qui permettent d'aboutir au résultat. Les processus max-stables étant des processus max-i.d, nous proposons un algorithme de simulation conditionnelle pour les champs max-stables puis nous l'utilisons pour des applications avec des données de précipitations autour de Zurich et de températures en Suisse. Nous trouvons aussi, une majoration du coefficient de β-mélange entre les restrictions d'un processus max-i.d sur deux sous-ensembles fermés et disjoints d'un espace métrique localement compact. Cette majoration permet d'obtenir de nouveaux critères pour le théorème de la limite central des processus stationnaires mélangeant. Enfin, nous terminons en démontrant qu'un processus stationnaire max-stable vérifiant la propriété de Markov est, quitte à renverser le temps, un processus max-autorégressif d’ordre 1. / The theme of this thesis is spatial extreme value theory and we focus on continuous max-stable processes. We begin with the convergence of the maximum of independent stochastic processes, by using the convergence of empirical measures to Poisson point processes. After that, we determine the regular conditional distributions of max infinitely divisible (max-i.d) processes. The representation of max-i.d. processes by Poisson point processes allows us to introduce the notions of extremal functions and hitting scenario. Our result relies on these new notions. Max-stable processes are max-i.d. processes, so we give an algorithm for conditional sampling and give an application to extreme precipitations around Zurich and extreme temperatures in Switzerland. We also find a upper bound for the β-mixing coefficient between the restrictions of a max-i.d. process on two disjoint closed subsets of a locally compact metric space. This entails a central limit theorem for stationary max-i.d processes. Finally, we prove that the class of stationary maxstable processes with the Markov property is equal, up to time reversal, to the class of stationary max-autoregressive processes of order 1.

對樣本資料之機率密度函數f(x)的無母數估計方法，一直是統計推論領域的研究重點之一，而且在通訊理論與圖形辨別上有非常重要的地位。傳統的文獻對密度函數的估計方法大部分著重於獨立樣本的情形。對於時間數列的相關樣本（例如：經濟指標或加權股票指數資料）比較少提到。本文針對具有弱相關性的穩定時間數列樣本，嘗試提出一個核密度估計的方法並探討其性質。 / For a sample data, the nonparametric estimation of a probability density f(x) is always one point of research problem in statistical inference and plays an important role in communication theory and pattern recognition. Traditionally, the literature dealing with density estimation when the observations are independent is extensive. Time series sample with weak dependence, (for example, an economic indicator or a stock market index data), less in this aspect of discussion. Our main purpose is concerned with the estimation of the probability density function f(x) of a stationary time series sample and discusses some properties of this kernel density.

Résumé : Il est bien connu que les lois marginales d'un vecteur aléatoire ne suffisent pas à caractériser sa distribution. Lorsque les lois marginales du vecteur aléatoire sont continues, le théorème de Sklar garantit l'existence et l'unicité d'une fonction appelée copule, caractérisant la dépendance entre les composantes du vecteur. La loi du vecteur aléatoire est parfaitement définie par la donnée des lois marginales et de la copule. Dans ce travail de thèse, nous proposons deux tests non paramétriques de détection de ruptures dans la distribution d’observations multivariées, particulièrement sensibles à des changements dans la copule des observations. Ils améliorent tous deux des propositions récentes et donnent lieu à des tests plus puissants que leurs prédécesseurs pour des classes d’alternatives pertinentes. Des simulations de Monte Carlo illustrent les performances de ces tests sur des échantillons de taille modérée. Le premier test est fondé sur une statistique à la Cramér-von Mises construite à partir du processus de copule empirique séquentiel. Une procédure de rééchantillonnage à base de multiplicateurs est proposée pour la statistique de test ; sa validité asymptotique sous l’hypothèse nulle est démontrée sous des conditions de mélange fort sur les données. Le second test se focalise sur la détection d’un changement dans le rho de Spearman multivarié des observations. Bien que moins général, il présente de meilleurs résultats en terme de puissance que le premier test pour les alternatives caractérisées par un changement dans le rho de Spearman. Deux stratégies de calcul de la valeur p sont comparées théoriquement et empiriquement : l’une utilise un rééchantillonnage de la statistique, l’autre est fondée sur une estimation de la loi limite de la statistique de test. // Abstract : It is very well-known that the marginal distributions of a random vector do not characterize the distribution of the random vector. When the marginal distributions are continuous, the work of Sklar ensures the existence and uniqueness of a function called copula which can be regarded as capturing the dependence between the components of the random vector. The cumulative distribution function of the vector can then be rewritten using only the copula and the marginal cumulative distribution functions. In this work, we propose two non-parametric tests for change-point detection, particularly sensitive to changes in the copula of multivariate time series. They improve on recent propositions and are more powerful for relevant alternatives involving a change in the copula. The finite-sample behavior of these tests is investigated through Monte Carlo experiments. The first test is based on a Cramér-von Mises statistic and on the sequential empirical copula process. A multiplier resampling scheme is suggested and its asymptotic validity under the null hypothesis is demonstrated under strong mixing conditions. The second test focuses on the detection of a change in Spearman’s rho. Monte Carlo simulations reveal that this test is more powerful than the first test for alternatives characterized by a change in Spearman’s rho. Two approaches to compute approximate p-values for the test are studied empirically and theoretically. The first one is based on resampling, the second one consists of estimating the asymptotic null distribution of the test statistic.

Il est bien connu que les lois marginales d'un vecteur aléatoire ne susent pas à caractériser sa distribution. Lorsque les lois marginales du vecteur aléatoire sont continues, le théorème de Sklar garantit l'existence et l'unicité d'une fonction appelée copule, caractérisant la dépendance entre les composantes du vecteur. La loi du vecteur aléatoire est parfaitement dénie par la donnée des lois marginales et de la copule. Dans ce travail de thèse, nous proposons deux tests non paramétriques de détection de ruptures dans la distribution d'observations multivariées, particulièrement sensibles à des changements dans la copule des observations. Ils améliorent tous deux des propositions récentes et donnent lieu à des tests plus puissants que leurs prédécesseurs pour des classes d'alternatives pertinentes. Des simulations de Monte Carlo illustrent les performances de ces tests sur des échantillons de taille modérée. Le premier test est fondé sur une statistique à la Cramér-von Mises construite à partir du processus de copule empirique séquentiel. Une procédure de rééchantillonnage à base de multiplicateurs est proposée pour la statistique de test ; sa validité asymptotique sous l'hypothèse nulle est démontrée sous des conditions de mélange fort sur les données. Le second test se focalise sur la détection d'un changement dans le rho de Spearman multivarié des observations. Bien que moins général, il présente de meilleurs résultats en terme de puissance que le premier test pour les alternatives caractérisées par un changement dans le rho de Spearman. Deux stratégies de calcul de la valeur p sont comparées théoriquement et empiriquement : l'une utilise un rééchantillonnage de la statistique, l'autre est fondée sur une estimation de la loi limite de la statistique de test. / It is very well-known that the marginal distributions of a random vector do not characterize the distribution of the random vector. When the marginal distributions are continuous, the work of Sklar ensures the existence and uniqueness of a function called copula which can be regarded as capturing the dependence between the components of the random vector. The cumulative distribution function of the vector can then be rewritten using only the copula and the marginal cumulative distribution functions. In this work, we propose two non-parametric tests for change-point detection, particularly sensitive to changes in the copula of multivariate time series. They improve on recent propositions and are more powerful for relevant alternatives involving a change in the copula. The finite-sample behavior of these tests is investigated through Monte Carlo experiments. The first test is based on a Cramér-von Mises statistic and on the sequential empirical copula process. A multiplier resampling scheme is suggested and its asymptotic validity under the null hypothesis is demonstrated under strong mixing conditions. The second test focuses on the detection of a change in Spearman's rho. Monte Carlo simulations reveal that this test is more powerful than the first test for alternatives characterized by a change in Spearman's rho. Two approaches to compute approximate p-values for the test are studied empirically and theoretically. The first one is based on resampling, the second one consists of estimating the asymptotic null distribution of the test statictic.

The use of Hilbert space theory became an important tool for ergodic theoreticians ever since John von Neumann proved the fundamental Mean Ergodic theorem in Hilbert space. Recurrence is one of the corner stones in the study of dynamical systems. In this dissertation some extended ideas besides those of the basic, well-known recurrence results are investigated. Hilbert space theory proves to be a very useful approach towards the solution of multiple recurrence problems in ergodic theory. Another very important use of Hilbert space theory became evident only relatively recently, when it was realized that non-commutative dynamical systems become accessible to the ergodic theorist through the important Gelfand-Naimark-Segal (GNS) representation of C*-algebras as Hilbert spaces. Through this construction we are enabled to invoke the rich catalogue of Hilbert space ergodic results to approach the more general, and usually more involved, non-commutative extensions of classical ergodic-theoretical results. In order to make this text self-contained, the basic, standard, ergodic-theoretical results are included in this text. In many instances Hilbert space counterparts of these basic results are also stated and proved. Chapters 1 and 2 are devoted to the introduction of these basic ergodic-theoretical results such as an introduction to the idea of measure-theoretic dynamical systems, citing some basic examples, Poincairé’s recurrence, the ergodic theorems of Von Neumann and Birkhoff, ergodicity, mixing and weakly mixing. In Chapter 2 several rudimentary results, which are the basic tools used in proofs, are also given. In Chapter 3 we show how a Hilbert space result, i.e. a variant of a result by Van der Corput for uniformly distributed sequences modulo 1, is used to simplify the proofs of some multiple recurrence problems. First we use it to simplify and clarify the proof of a multiple recurrence result by Furstenberg, and also to extend that result to a more general case, using the same Van der Corput lemma. This may be considered the main result of this thesis, since it supplies an original proof of this result. The Van der Corput lemma helps to simplify many of the tedious terms that are found in Furstenberg’s proof. In Chapter 4 we list and discuss a few important results where classical (commutative) ergodic results were extended to the non-commutative case. As stated before, these extensions are mainly due to the accessibility of Hilbert space theory through the GNS construction. The main result in this section is a result proved by Niculescu, Ströh and Zsidó, which is proved here using a similar Van der Corput lemma as in the commutative case. Although we prove a special case of the theorem by Niculescu, Ströh and Zsidó, the same method (Van der Corput) can be used to prove the generalized result. Copyright 2004, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. Please cite as follows: Beters, FJC 2004, A Hilbert space approach to multiple recurrence in ergodic theory, MSc dissertation, University of Pretoria, Pretoria, viewed yymmdd < http://upetd.up.ac.za/thesis/available/etd-02222006-104936 / > / Dissertation (MSc (Applied Mathematics))--University of Pretoria, 2007. / Mathematics and Applied Mathematics / unrestricted