Cette thèse porte sur inférence statistique, les méthodes bootstrap et l’analyse multivariée dans le cadre des processus semi-markoviens. Les applications principales concernent un problème de la mécanique de la rupture. Ce travail a une contribution double. La première partie concerne la modélisation stochastique du phénomène de la propagation de fissure de fatigue. Une équation différentielle stochastique décrit le mécanisme de la dégradation et le caractère aléatoire inné du phénomène est traité par un processus de perturbation. Sous l'hypothèse que ce processus soit un processus markovien (ou semi-markovien) de saut, la fiabilité du modèle est étudiée en faisant usage de la théorie du renouvellement markovien et une nouvelle méthode, plus rapide, de calcul de fiabilité est proposée avec l'algorithme correspondant. La méthode et le modèle pour le processus markovien de perturbation sont validés sur des données expérimentales. Ensuite, la consistance forte des estimateurs des moindres carrés des paramètres du modèle est obtenue en supposant que les résidus du modèle stochastique de régression, dans lequel le modèle initial est transformé, soient des différences de martingales. Dans la deuxième partie de la thèse, nous avons abordé le problème difficile de l'approximation de la distribution limite de certains estimateurs non paramétriques des noyaux semi-markoviens ou certaines fonctionnelles via la méthode bootstrap pondérée dans un cadre général. Des applications de ces résultats sur des problèmes statistiques sont données pour la construction de bandes de confiance, les tests statistiques, le calcul de la valeur p du test et pour l’estimation des inverses généralisés. / The present dissertation is devoted to the statistical inference, bootstrap methods and multivariate analysis in the framework of semi-Markov processes. The main applications concern a mechanical problem from fracture mechanics. This work has a two-fold contribution. The first part concerns in general the stochastic modeling of the fatigue crack propagation phenomenon. A stochastic differential equation describes the degradation mechanism and the innate randomness of the phenomenon is handled by a perturbation process. Under the assumption that this process is a jump Markov (or semi-Markov) process, the reliability of the model is studied by means of Markov renewal theory and a new, faster, reliability calculus method is proposed with the respective algorithm. The method and the model for the Markov perturbation process are validated on experimental fatigue data. Next, the strong consistency of the least squares estimates of the model parameters is obtained by assuming that the residuals of the stochastic regression model are martingale differences into which the initial model function is transformed. In the second part of the manuscript, we have tackled the difficult problem of approximating the limiting distribution of certain non-parametric estimators of semi-Markov kernels or some functionals of them via the weighted bootstrap methodology in a general framework. Applications of these results on statistical problems such as the construction of confidence bands, the statistical tests, the computation of the p-value of the test are provided and the estimation of the generalized inverses.

Safety analysis is critical when developing new engineering systems. Many systems have to function under randomly occurring events, making stochastic processes useful in a safety modelling context. However, a general stochastic process is very challenging to analyse mathematically. Therefore, model restrictions are necessary to simplify the mathematical analysis. A popular simplified stochastic model is the Semi-Markov process (SMP), which is a generalization of the "memoryless" continuous-time Markov chain. However, only a subclass of Semi-Markov models can be analysed with non-simulation based methods. In these models, the cumulative density function (cdf) of the random variables describing the system is in the form of expolynomials. This thesis investigates the possibility to extend the number of Semi-Markov models that can be analysed with non-simulation based methods by approximating the non-expolynomial random variables with expolynomials. This thesis focus on approximation of models partially described by LogNormal and Weibull distributed random variables. The result shows that it is possible to approximate some Semi-Markov models with non-expolynomial random variables. However, there is an increasing difficulty in approximating a non-expolynomial random variable when the variability in the distribution increases. / Säkerhetsanalys är avgörande när man utvecklar nya tekniska system. Många system måste fungera under slumpmässigt inträffande händelser, vilket gör stokastiska processer användbara i ett säkerhetsmodellerande sammanhang. En allmän stokastisk process är dock mycket utmanande att analysera matematiskt. Därför är begränsningar på modellen nödvändiga för att förenkla den matematiska analysen. En populär förenklad stokastisk modell är Semi-Markov-processen (SMP), vilket är en generalisering av den "minneslösa" tids-kontinuerliga Markov-kedjan. Dock är det endast en underklass av Semi-Markov-modeller som kan analyseras med icke-simuleringsbaserade metoder. I dessa modeller är den kumulativa densitetsfunktionen (cdf) för de slumpmässiga variablerna som beskriver systemet i form av expolynomials. Denna rapport undersöker möjligheten att utöka antalet Semi-Markov-modeller som kan analyseras med icke-simuleringsbaserade metoder genom att approximera de icke-expolynomial slumpvariablerna med expolynomials. Vi fokuserar på approximering av modeller som delvis beskrivs av LogNormal distribuerade och Weibull distribuerade slumpmässiga variabler. Resultatet visar att det är möjligt att approximera vissa stokastiska variabler som är icke-expolynomial i Semi-Markov-modeller. Resultatet visar dock att det är en ökande svårighet att approximera en icke-expolynomial slumpmässiga variabeln när variabiliteten i fördelningen ökar.

This research investigates existing relationships between the three apparently unrelated subjects: Markov process, Semigroups and Partial difierential equations. Markov processes define semigroups through their transition functions. Conversely particular semigroups determine transition functions and can be regarded as Markov processes. We have exploited these relationships to study some Markov chains. The infnitesimal generator of a Feller semigroup on the closure of a bounded domain of Rn; (n ^ 2), is an integro-diferential operator in the interior of the domain and verifes a boundary condition. The existence of a Feller semigroup defined by a diferential operator and a boundary condition is due to the existence of solution of a bounded value problem. From this result other existence suficient conditions on the existence of Feller semigroups have been obtained and we have applied some of them to construct Feller semigroups on the unity disk of R2. / Decision Sciences / M. Sc. (Operations Research)

Thesis (MSc)--Stellenbosch University, 2011. / ENGLISH ABSTRACT: In any ecological system, organisms need to interact with each other for their survival. Such interactions form ecological networks which are usually very complex. Nevertheless, they exhibit well de ned patterns; these regularities are often interpreted as products of meaningful ecological processes. As the networks are evolving through time, biological evolution is one of the factors that affects ecological network architecture. In this work, we develop a mathematical model that represents the evolution through time of such ecological interaction networks. The problem is approached by modelling network evolution as a continuous time Markov process, in such a way that the interactions in which a parent species is involved are potentially inherited by its descendant species. This approach allows us to infer ecological parameters and ecological network histories from real-world network data, as well as to simulate ecological networks under our model. While ecologists have long been aware of the in uence of evolutionary processes in shaping ecological networks, we are now able to evaluate the importance of such in uence. / AFRIKAANSE OPSOMMING: In enige ekologiese stelsel benodig organismes wisselwerkings met mekaar ten einde te oorleef. Sulke interaksies vorm ekologiese netwerke wat gewoonlik baie kompleks is maar nogtans goed-gede nieerde patrone vertoon. Hierdie patrone word dikwels geïnterpreteer as die produk van betekenisvolle ekologiese prosesse. Aangesien die netwerke met die verloop van tyd ontwikkel, is biologiese ewolusie een van die faktore wat ekologiese netwerkargitektuur beïnvloed. In hierdie studie ontwikkel ons 'n wiskundige model wat die ewolusie van sulke ekologiese interaksienetwerke voorstel. Die probleem word benader deur netwerkewolusie as 'n kontinue-tyd Markov-proses te modelleer, op so 'n manier dat die interaksies waarin 'n voorouerspesie betrokke is potensieel oorerf kan word deur die afstammelingspesies. Hierdie benadering laat ons toe om ekologiese parameters en ekologiese netwerkgeskiedenisse vanuit regte-wêreld data af te lei, sowel as om ekologiese netwerke onder ons model te simuleer. Alhoewel ekoloë al lank reeds bewus is van die invloed wat ewolusionêre prosesse het op die vorming van ekologiese netwerke, is ons nou in staat om die belangrikheid van hierdie invloed te evalueer.

Thesis (MSc)--Stellenbosch University, 2012. / ENGLISH ABSTRACT: This work employs perturbation techniques to price and hedge financial derivatives in a stochastic volatility framework. Fouque et al. [44] model volatility as a function of two processes operating on different time-scales. One process is responsible for the fast-fluctuating feature of volatility and corresponds to the slow time-scale and the second is for slowfluctuations or fast time-scale. The former is an Ergodic Markov process and the latter is a strong solution to a Lipschitz stochastic differential equation. This work mainly involves modelling, analysis and estimation techniques, exploiting the concept of mean reversion of volatility. The approach used is robust in the sense that it does not assume a specific volatility model. Using singular and regular perturbation techniques on the resulting PDE a first-order price correction to Black-Scholes option pricing model is derived. Vital groupings of market parameters are identified and their estimation from market data is extremely efficient and stable. The implied volatility is expressed as a linear (affine) function of log-moneyness-tomaturity ratio, and can be easily calibrated by estimating the grouped market parameters from the observed implied volatility surface. Importantly, the same grouped parameters can be used to price other complex derivatives beyond the European and American options, which include Barrier, Asian, Basket and Forward options. However, this semi-analytic perturbative approach is effective for longer maturities and unstable when pricing is done close to maturity. As a result a more accurate technique, the decomposition pricing approach that gives explicit analytic first- and second-order pricing and implied volatility formulae is discussed as one of the current alternatives. Here, the method is only employed for European options but an extension to other options could be an idea for further research. The only requirements for this method are integrability and regularity of the stochastic volatility process. Corrections to [3] remarkable work are discussed here. / AFRIKAANSE OPSOMMING: Hierdie werk gebruik steuringstegnieke om finansiële afgeleide instrumente in ’n stogastiese wisselvalligheid raamwerk te prys en te verskans. Fouque et al. [44] gemodelleer wisselvalligheid as ’n funksie van twee prosesse wat op verskillende tyd-skale werk. Een proses is verantwoordelik vir die vinnig-wisselende eienskap van die wisselvalligheid en stem ooreen met die stadiger tyd-skaal en die tweede is vir stadig-wisselende fluktuasies of ’n vinniger tyd-skaal. Die voormalige is ’n Ergodiese-Markov-proses en die laasgenoemde is ’n sterk oplossing vir ’n Lipschitz stogastiese differensiaalvergelyking. Hierdie werk behels hoofsaaklik modellering, analise en skattingstegnieke, wat die konsep van terugkeer to die gemiddelde van die wisseling gebruik. Die benadering wat gebruik word is rubuust in die sin dat dit nie ’n aanname van ’n spesifieke wisselvalligheid model maak nie. Deur singulêre en reëlmatige steuringstegnieke te gebruik op die PDV kan ’n eerste-orde pryskorreksie aan die Black-Scholes opsie-waardasiemodel afgelei word. Belangrike groeperings van mark parameters is geïdentifiseer en hul geskatte waardes van mark data is uiters doeltreffend en stabiel. Die geïmpliseerde onbestendigheid word uitgedruk as ’n lineêre (affiene) funksie van die log-geldkarakter-tot-verval verhouding, en kan maklik gekalibreer word deur gegroepeerde mark parameters te beraam van die waargenome geïmpliseerde wisselvalligheids vlak. Wat belangrik is, is dat dieselfde gegroepeerde parameters gebruik kan word om ander komplekse afgeleide instrumente buite die Europese en Amerikaanse opsies te prys, dié sluit in Barrier, Asiatiese, Basket en Stuur opsies. Hierdie semi-analitiese steurings benadering is effektief vir langer termyne en onstabiel wanneer pryse naby aan die vervaldatum beraam word. As gevolg hiervan is ’n meer akkurate tegniek, die ontbinding prys benadering wat eksplisiete analitiese eerste- en tweede-orde pryse en geïmpliseerde wisselvalligheid formules gee as een van die huidige alternatiewe bespreek. Hier word slegs die metode vir Europese opsies gebruik, maar ’n uitbreiding na ander opsies kan’n idee vir verdere navorsing wees. Die enigste vereistes vir hierdie metode is integreerbaarheid en reëlmatigheid van die stogastiese wisselvalligheid proses. Korreksies tot [3] se noemenswaardige werk word ook hier bespreek.

Esta tese trata do problema de controle ótimo estocástico de sistemas com saltos Markovianos e ruído multiplicativo a tempo discreto, com horizontes de tempo finito e infinito. A função custo é composta de termos quadráticos e lineares nas variáveis de estado e de controle, com matrizes peso indefinidas. Como resultado principal do problema com horizonte finito, é apresentada uma condição necessária e suficiente para que o problema de controle seja bem posto, a partir da qual uma solução ótima é derivada. A condição e a lei de controle são escritas em termos de um conjunto acoplado de equações de Riccati interconectadas a um conjunto acoplado de equações lineares recursivas. Para o caso de horizonte infinito, são apresentadas as soluções ótimas para os problemas de custo médio a longo prazo e com desconto, derivadas a partir de uma solução estabilizante de um conjunto de equações algébricas de Riccati acopladas generalizadas (GCARE). A existência da solução estabilizante é uma condição suficiente para que tais problemas sejam do tipo bem posto. Além disso, são apresentadas condições para a existência das soluções maximal e estabilizante do sistema GCARE. Como aplicações dos resultados obtidos, são apresentadas as soluções de um problema de otimização de carteiras de investimento com benchmark e de um problema de gestão de ativos e passivos de fundos de pensão do tipo benefício definido, ambos os casos com mudanças de regime nas variáreis de mercado. / This thesis considers the finite-horizon and infinite-horizon stochastic optimal control problem for discrete-time Markov jump with multiplicative noise linear systems. The performance criterion is assumed to be formed by a linear combination of a quadratic part and a linear part in the state and control variables. The weighting matrices of the state and control for the quadratic part are allowed to be indefinite. For the finite-horizon problem the main results consist of deriving a necessary and sufficient condition under which the problem is well posed and a optimal control law is derived. This condition and the optimal control law are written in terms of a set of coupled generalized Riccati difference equations interconnected with a set of coupled linear recursive equations. For the infinite-horizon problem a set of generalized coupled algebraic Riccati equations (GCARE) is studied. In this case, a sufficient condition under which there exists the maximal solution and a necessary and sufficient condition under which there exists the mean square stabilizing solution for the GCARE are presented. Moreover, a solution for the discounted and long run average cost problems is presented. The results obtained are applied to solver a portfolio optimization problem with benchmark and a pension fund problem with regime switching.

Investiga-se, em tempo discreto, o problema multi-período de otimização de carteiras generalizado em média-variância cujos coeficientes de mercado são modulados por uma cadeia de Markov finita. O problema multi-período generalizado de média-variância com saltos Markovianos (PGMV ) é um problema de controle estocástico sem restrição cuja função objetivo consiste na maximização da soma ponderada ao longo do tempo da combinação linear de três elementos: o valor esperado da riqueza do investidor, o quadrado da esperança desta riqueza e a esperança do quadrado deste patrimônio. A principal contribuição deste trabalho é a derivação analítica de condições necessárias e suficientes para a determinação de uma estratégia ótima de investimento para o problema PGMV . A partir deste modelo são derivadas várias formulações de médiavariância, como o modelo tradicional cujo objetivo é maximizar o valor esperado da riqueza final do investidor, dado um nível de risco (variância) do portfólio no horizonte de investimento, bem como o modelo mais complexo que busca maximizar a soma ponderada das esperanças da riqueza ao longo do tempo, limitando a perda deste patrimônio em qualquer momento. Adicionalmente, derivam-se formas fechadas para a solução dos problemas citados quando as restrições incidem somente no instante final. Outra contribuição deste trabalho é a extensão do modelo PGMV para a solução do problema de seleção de carteiras em média-variância com o objetivo de superar um benchmark estocástico, com restrições sobre o valor esperado ou sobre a variância do tracking error do portfólio. Por fim, aplicam-se os resultados obtidos em exemplos numéricos cujo universo de investimento são todas as ações do IBOVESPA. / In this work we deal with a discrete-time multi-period mean-variance portfolio selection model with the market parameters subject to Markov regime switching. The multi-period generalized mean-variance portfolio selection model with regime switching (PGMV ) is an unrestricted stochastic control problem, in which the objective function involves the maximization of the weighted sum of a linear combination of three parts: the expected wealth, the square of the expected wealth and the expected value of the wealth squared. The main contribution of this work is the analytical derivation of necessary and sufficient conditions for the existence of an optimal control strategy to this PGMV model. We show that several mean-variance models are derived from the PGMV model, as the traditional formulation in which the objective is to maximize the expected terminal wealth for a given final risk (variance), or the complex one in which the objective function is to maximize the weighted sum of the wealth throughout its investment horizon, with control over maximum wealth lost. Additionally, we derive closed forms solutions for the above models when the restrictions are just in the final time. Another contribution of this work is to extend the PGMV model to solve the multi-period portfolio selection problem of beating a stochastic benchmark with control over the tracking error variance or its expected value. Finally, we run numerical examples in which the investment universe is formed by all the stocks belonging to the IBOVESPA.

We propose a model for an insurance loss index and the claims process of a single insurance company holding a fraction of the total number of contracts that captures both ordinary losses and losses due to catastrophes. In this model we price a catastrophe derivative by the method of utility indifference pricing. The associated stochastic optimization problem is treated by techniques for piecewise deterministic Markov processes. A numerical study illustrates our results.

Submitted by admin tede (tede@pucgoias.edu.br) on 2017-08-21T12:30:58Z No. of bitstreams: 1 Celso Aurélio de Morais Lima.pdf: 2546394 bytes, checksum: 8a8908066e6f60ae202da67d1738b90d (MD5) / Made available in DSpace on 2017-08-21T12:30:58Z (GMT). No. of bitstreams: 1 Celso Aurélio de Morais Lima.pdf: 2546394 bytes, checksum: 8a8908066e6f60ae202da67d1738b90d (MD5) Previous issue date: 2017-04-27 / The main objective of this dissertation is to develop a reliability assessment applied to reparable systems in the sugar and alcohol industry. The work has a quantitative approach with a combined research method: simulation modeling with case-study. Therefore, a dynamic modeling is used to develop a case-study. For this, a Non- Homogeneous Markov Process (PNHM) model is used to represent the states transitions (operation-maintenance) of sugar centrifuges, in order to obtain reliability indicators. Integrated to the PNHM model, it will be used the Generalized Renewal Process (PRG) to describe the probabilities of failures considering imperfect repairs. The PRG is defined according to the parameters of scale, shape and rejuvenation (α, β, q), which are estimated by Bayesian Inference. In the development of the case-study, the data collection of centrifugal failures was performed and, through the simulation of the hybrid model, the case-study was conceived. The estimated availability for 5640 hours was 93.23%, whose the other 7% represents maintenances moments. For 323 hours of simulation, the reliability resulting was 50%, demonstrating high system susceptibility to failures. The results suggest the revisions of the intervals defined for preventives maintenances, which should be applied to the most observed failure mode, called malfunction of the sensing systems. / O principal objetivo desta dissertação é desenvolver uma avaliação de confiabilidade aplicada a sistemas reparáveis, na indústria sucroalcooleira. O trabalho possui abordagem quantitativa com método de pesquisa combinado: modelagem de simulação com estudo de caso. Portanto, utilizar-se-á de uma modelagem dinâmica para desenvolver um estudo de caso. Para isso, aplicar-se-á um modelo de Processos Não Homogêneos de Markov (PNHM) para representar as transições entre estados (operacional-em manutenção) das centrífugas de açúcar, visando obter indicadores de confiabilidade. Integrado ao modelo PNHM, será utilizado o Processo de Renovação Generalizado (PRG) para descrever as probabilidades de falhas considerando reparos imperfeitos. O PRG é definido em função dos parâmetros de escala, forma e rejuvenescimento ( ,!,"), que serão estimados via Inferência Bayesiana. No desenvolvimento do estudo de caso, realizou-se a coleta de dados de falhas das centrífugas e, por meio da simulação do modelo híbrido, o estudo de caso foi concebido. A disponibilidade estimada para 5640 horas foi de 93,23%, sendo os 7% complementares referentes a manutenções. A confiabilidade apresentada foi de 50% para 323 horas, demonstrando alta suscetibilidade do sistema à falhas. Os resultados sugerem revisão nos intervalos definidos para manutenção preventiva, as quais deverão ser dedicadas ao modo de falha mais observado, denominado mal funcionamento dos sistemas de sensoreamento.

Submitted by Maria Cristina (library@lncc.br) on 2018-06-27T12:31:36Z No. of bitstreams: 1 Dissertacao_final_Fortia.pdf: 758629 bytes, checksum: 6b31d1df1ed8f464b298cce7e1ee4180 (MD5) / Approved for entry into archive by Maria Cristina (library@lncc.br) on 2018-06-27T12:31:54Z (GMT) No. of bitstreams: 1 Dissertacao_final_Fortia.pdf: 758629 bytes, checksum: 6b31d1df1ed8f464b298cce7e1ee4180 (MD5) / Made available in DSpace on 2018-06-27T12:32:06Z (GMT). No. of bitstreams: 1 Dissertacao_final_Fortia.pdf: 758629 bytes, checksum: 6b31d1df1ed8f464b298cce7e1ee4180 (MD5) Previous issue date: 2017-02-24 / Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) / Stochastic differential equations with Markovian jump parameters constitute one of the most important class of hybrid dynamical systems, which has been extensively used for the modeling of dynamical systems which are subject to abrupt changes in their structure. The abrupt changes can be due, for instance, to abrupt environmental disturbances, component failure, volatility in economic systems, changes in subsystems interconnections, abrupt changes in the operation of a nonlinear plant, etc. This can be found, for instance, in aircraft control systems, robot systems, large flexible structure for space station, etc. We shall be particularly interested in the linear class which is dubbed in the literature as the class of Markov jump linear systems (MJLS). The jump mechanism is modeled by a Markov process, which is also known in the literature as the operation mode. The dissertation address the filtering problem of the operation mode for the class of MJLS. Previous result in the literature on this problem has been obtained by Wonham, which has shown the existence of an optimal nonlinear filter for this problem. The main hindrance with Wonham’s result, in the context of the control problem with partial observation of operation mode, is that it introduces a great deal of nonlinearity in the Hamilton-Jacobi- Belman equation, which makes it difficult to get an explicit closed solution for the control problem. Motivated by this, the main contribution of this dissertation is to devise an optimal linear filter for the mode operation, which we believe could be more favorable in the solution of the control problem with partial observations. In addition, relying on Murayama’s stochastic numerical method and the results of Yuan and Mao, we carry out simulation of Wonham’s filter, and the one devised in the dissertation, in order to compare their performances. / As equações diferenciais estocáticas com salto Markoviano constituem uma das clases de sistemas dinâmicos híbridos mais importantes, e tem sido muito usados para modelar sistemas sujeitos a mudanças abruptas na sua estructura. Essas mudanças podem ser devido a, por exemplo, perturbações ambientais, falhas em componentes, volatilidade em sistemas econômicos, mudanças em interconexões de subsistemas, mudanças abruptas em operações de plantas não lineares, etc. Estas falhas podem ser encontradas em sistemas de controle para aeronaves, sistemas robóticos, estructuras grandes e flexíveis em estações espaciais, etc. Nós estamos especialmente interessados na clase de sistemas lineares que é referenciada na literatura como sistemas lineares com salto Markoviano (SLSM). O mecanismo de salto é modelado por um processo de Markov, que é conhecido na literatura como modo de operação do sistema. Essa dissertação visa o problema de filtragem para o modo de operação do sistema linear com salto. Na literatura pode-se encontrar resultados já obtidos para esse problema como é o caso do filtro ótimo não linear deduzido por Wonham. Mas no contexto de controle ótimo com observações parciais do modo de operação, o filtro de Wonham introduz não linearidades na equação de Hamilton-Jacobi-Belman, fazendo com que seja muito complexo obter uma solução fechada para o problema de controle. A principal motivação desta dissertação é deduzir o filtro ótimo linear para o modo de operação, já que esta pode ser uma solução mais favorável para o problema de controle ótimo. Finalmente, usando o método numérico para equações diferenciais estocásticas de Euler-Murayama e o resultado de Yuan e Mao, realizamos a simulação do filtro de Wonham tal como o filtro deduzido neste trabalho, com o objetivo de comparar as respectivas performances.