Passeio aleatório é uma classe de modelos matemáticos que têm por objetivo descrever processos estocásticos cujo resultado observável é dado por uma soma de variáveis aleatórias. O termo foi cunhado em 1905 pelo estatístico inglês Karl Pearson, estando na época interessado na modelagem da migração de insetos, e hoje possui uma ampla gama de aplicações, indo desde a biologia, passando pela física e química, e chegando na economia. Tendo sido estudado por inúmeros cientistas, muitas variações surgiram, chegando aos passeios aleatórios correlacionados, processos estocásticos não-Markovianos nos quais as variáveis aleatórias que se somam, chamadas de passos, possuem dependências umas com as outras, com correlações de caudas longas. Em 2004, surge na literatura o passeio aleatório do elefante, um passeio aleatório correlacionado com um mecanismo microscópico de memória de longo alcance muito bem definido e com soluções analíticas. Além desses dois fatos, também despertou o interesse da comunidade científica por exibir superdifusão. Muitas variações desse modelo foram propostas e vários resultados foram obtidos nos anos que se seguiram. A presente dissertação contem uma compilação dos principais modelos e resultados da área, tentando ser um texto introdutório ao assunto, focando sempre no que diz respeito à difusão. No caso unidimensional, propomos uma generalização desse tipo de passeio aleatório, o qual envolve decisões probabilísticas com respeito a passos lembrados do passado. Já no caso multi-muldimensional, apresentamos o conceito de acoplamento de memória e o modelo de Vaca e Boi, introduzidos pelo autor deste trabalho em 2018, como uma maneira de incluir interações entre elefantes. Também obtivemos um limite do contínuo para esse último processo, permitindo calcular os regimes de difusão para o Boi e construir um diagrama de fases para o mesmo. Esses últimos pontos constituem as principais contribuições do presente trabalho. / Random walk is a class of mathematical models which has the objective of describing a stochastic process whose observable result is given by a sum of aleatory variables. The term was coined in 1905 by the english statistician Karl Pearson while he was interested in the insects migration modeling, but today it has a myriad of applications, from biology to stock markets, passing through physics and chemestry. It has been studied by an uncountable number of scientists and a lot of variations have appeared, including those called correlated random walks, which are stochastic non-Markovian process in which those random variables that are summed, called steps, depends one of each other with fat tails correlations. In 2004, the elephant random walk appeared in the literature. It is a correlated random walk with a microscopic well defined memory mechanism and that has analitical solutions. Besides these facts, it also arouse the interest of scientific community because it exhibits superdifusion behaviour. In the one-dimensional case, we propose a generalization of this kind of random walk, which involves probabilistic decisions with respect to remembered steps given in the past. In the multi-dimensional case, we present the concept of memory coupling and the Cow and Ox model, which were introduced by the author of this work in 2018 as a manner of including interactions among elephants. We have also obtained a continuum limit of this process, allowing us to calculate the Ox diffusion regimes and to build its phase diagram. These last points constitute the main contributions of the present work.

In the presence of a solid-liquid or liquid-air interface, bacteria can choose between a planktonic and a sessile lifestyle. Depending on environmental conditions, cells swimming in close proximity to the interface can irreversibly attach to the surface and grow into three-dimensional aggregates where the majority of cells is sessile and embedded in an extracellular polymer matrix (biofilm). We used microfluidic tools and time lapse microscopy to perform experiments with the polarly flagellated soil bacterium Pseudomonas putida (P. putida), a bacterial species that is able to form biofilms. We analyzed individual trajectories of swimming cells, both in the bulk fluid and in close proximity to a glass-liquid interface. Additionally, surface related growth during the early phase of biofilm formation was investigated. In the bulk fluid, P.putida shows a typical bacterial swimming pattern of alternating periods of persistent displacement along a line (runs) and fast reorientation events (turns) and cells swim with an average speed around 24 micrometer per second. We found that the distribution of turning angles is bimodal with a dominating peak around 180 degrees. In approximately six out of ten turning events, the cell reverses its swimming direction. In addition, our analysis revealed that upon a reversal, the cell systematically changes its swimming speed by a factor of two on average. Based on the experimentally observed values of mean runtime and rotational diffusion, we presented a model to describe the spreading of a population of cells by a run-reverse random walker with alternating speeds. We successfully recover the mean square displacement and, by an extended version of the model, also the negative dip in the directional autocorrelation function as observed in the experiments. The analytical solution of the model demonstrates that alternating speeds enhance a cells ability to explore its environment as compared to a bacterium moving at a constant intermediate speed. As compared to the bulk fluid, for cells swimming near a solid boundary we observed an increase in swimming speed at distances below d= 5 micrometer and an increase in average angular velocity at distances below d= 4 micrometer. While the average speed was maximal with an increase around 15% at a distance of d= 3 micrometer, the angular velocity was highest in closest proximity to the boundary at d=1 micrometer with an increase around 90% as compared to the bulk fluid. To investigate the swimming behavior in a confinement between two solid boundaries, we developed an experimental setup to acquire three-dimensional trajectories using a piezo driven objective mount coupled to a high speed camera. Results on speed and angular velocity were consistent with motility statistics in the presence of a single boundary. Additionally, an analysis of the probability density revealed that a majority of cells accumulated near the upper and lower boundaries of the microchannel. The increase in angular velocity is consistent with previous studies, where bacteria near a solid boundary were shown to swim on circular trajectories, an effect which can be attributed to a wall induced torque. The increase in speed at a distance of several times the size of the cell body, however, cannot be explained by existing theories which either consider the drag increase on cell body and flagellum near a boundary (resistive force theory) or model the swimming microorganism by a multipole expansion to account for the flow field interaction between cell and boundary. An accumulation of swimming bacteria near solid boundaries has been observed in similar experiments. Our results confirm that collisions with the surface play an important role and hydrodynamic interactions alone cannot explain the steady-state accumulation of cells near the channel walls. Furthermore, we monitored the number growth of cells in the microchannel under medium rich conditions. We observed that, after a lag time, initially isolated cells at the surface started to grow by division into colonies of increasing size, while coexisting with a comparable smaller number of swimming cells. After 5:50 hours, we observed a sudden jump in the number of swimming cells, which was accompanied by a breakup of bigger clusters on the surface. After approximately 30 minutes where planktonic cells dominated in the microchannel, individual swimming cells reattached to the surface. We interpret this process as an emigration and recolonization event. A number of complementary experiments were performed to investigate the influence of collective effects or a depletion of the growth medium on the transition. Similar to earlier observations on another bacterium from the same family we found that the release of cells to the swimming phase is most likely the result of an individual adaption process, where syntheses of proteins for flagellar motility are upregulated after a number of division cycles at the surface. / Bakterien sind einzellige Mikroorganismen, die sich in flüssigem Medium mit Hilfe von rotierenden Flagellen, länglichen Fasern aus Proteinen, schwimmend fortbewegen. In Gegenwart einer Grenzfläche und unter günstigen Umweltbedingungen siedeln sich Bakterien an der Oberfläche an und gehen in eine sesshafte Wachstumsphase über. Die Wachstumsphase an der Oberfläche ist gekennzeichnet durch das Absondern von klebrigen, nährstoffreichen extrazellulären Substanzen, welche die Verbindung der Bakterien untereinander und mit der Oberfläche verstärken. Die entstehenden Aggregate aus extrazellulärer Matrix und Bakterien werden als Biofilm bezeichnet. In der vorliegenden Arbeit untersuchten wir ein Bodenbakterium, Pseudomonas putida (P. putida), welches in wässriger Umgebung an festen Oberflächen Biofilme ausbildet. Wir benutzten photolithographisch hergestellte Mikrokanäle und Hochgeschwindigkeits-Videomikroskopie um die Bewegung schwimmender Zellen in verschiedenen Abständen zu einer Glasoberfläche aufzunehmen. Zusätzlich wurden Daten über das parallel stattfindende Wachstum der sesshaften Zellen an der Oberfläche aufgezeichnet. Die Analyse von Trajektorien frei schwimmender Zellen zeigte, dass sich Liniensegmente, entlang derer sich die Zellen in eine konstante Richtung bewegen, mit scharfen Kehrtwendungen mit einem Winkel von 180 Grad abwechseln. Dabei änderte sich die Schwimmgeschwindigket von einem zum nächsten Segment im Mittel um einen Faktor von 2. Unsere experimentellen Daten waren die Grundlage für ein mathematisches Modell zur Beschreibung der Zellbewegung mit alternierender Geschwindigkeit. Die analytische Lösung des Modells zeigt elegant, dass eine Population von Bakterien, welche zwischen zwei Geschwindigkeiten wechseln, signifikant schneller expandiert als eine Referenzpopulation mit Bakterien konstanter Schwimmgeschwindkeit. Im Vergleich zu frei schwimmenden Bakterien beobachteten wir in der Nähe der Oberfläche eine um 15% erhöhte Schwimmgeschwindigkeit der Zellen und eine um 90 % erhöhte Winkel-geschwindigkeit. Außerdem wurde eine signifikant höhere Zelldichte in der Nähe der Grenzfläche gemessen. Während sich der Anstieg in der Winkelgeschwindigkeit durch ein Drehmoment erklären lässt, welches in Oberflächennähe auf den rotierenden Zellkörper und die rotierenden Flagellen wirkt, kann die Beschleunigung und Akkumulation der Zellen bei dem beobachteten Abstand nicht durch existierende Theorien erklärt werden. Unsere Ergebnisse lassen vermuten, dass neben hydrodynamischen Effekten auch Kollisionen mit der Oberfläche eine wichtige Rolle spielen und sich die Rotationsgeschwindigkeit der Flagellenmotoren in der Nähe einer festen Oberfläche grundsätzlich verändert. Unsere Experimente zum Zellwachstum an Oberflächen zeigten, dass sich etwa sechs Stunden nach Beginn des Experiments größere Kolonien an der Kanaloberfläche auflösen und Zellen für ca. 30 Minuten zurück in die schwimmende Phase wechseln. Ergebnisse von mehreren Vergleichsexperimenten deuten darauf hin, dass dieser Übergang nach einer festen Anzahl von Zellteilungen an der Oberfläche erfolgt und nicht durch den Verbrauch des Wachstumsmediums bedingt wird.

A pesquisa apresenta um estudo sobre a superioridade dos analistas de mercado com relação aos modelos random walk na previsão de resultados futuros das empresas brasileiras de capital aberto a curto e longo prazo. A literatura tradicional indica superioridade irrestrita dos analistas de mercado sobre os modelos de séries temporais por conta das vantagens de tempo e informação desses agentes. No entanto, estudos recentes da literatura internacional apontam para a necessidade de reavaliação dessa superioridade indicando que, para determinadas características da empresa e principalmente para estimativas de longo prazo, não se verifica superioridade dos analistas com relação aos modelos de séries temporais. Partindo desses achados, essa pesquisa defende a TESE de que para o caso brasileiro a superioridade dos analistas não é irrestrita. Este trabalho avalia as previsões de lucro dos analistas e dos modelos random walk, simples e com crescimento, a curto e longo prazo, para as empresas brasileiras de capital aberto no período de 2010 a 2015. Os dados foram obtidos via plataforma da Thomson Reuters®, nas bases de dados do I/B/E/S® e Thomson Financial. Seguindo a literatura, foram utilizados testes de diferença de média. Como diferencial da pesquisa, foi realizada uma análise de dados em painel no sentido de permitir uma avaliação mais precisa sobre os determinantes da superioridade dos analistas para o caso brasileiro. Ainda, foi proposto um modelo de regressão linear simples para avaliar o conteúdo informacional das previsões dos analistas de mercado e dos modelos random walk. Os resultados indicam: i) maior acurácia de previsão paras os modelos random walk simples quando comparados com os modelos de random walk com crescimento; ii) para a amostra total, nota-se maior acurácia da previsão dos modelos random walk a curto e longo prazo, com superioridade dos analistas apenas para previsões com três meses de defasagem; iii) além da defasagem de previsão, a variabilidade dos lucros, a quantidade de analistas, a dispersão das estimativas dos analistas, o tamanho da empresa, o resultado positivo ou negativo, a listagem em índice de mercado e a idade da empresa no mercado de capitais são fatores que alteram a superioridade dos analistas para o caso brasileiro; iv) maior conteúdo informacional das previsões random walk para previsão de lucros futuros das empresas. Esses resultados são importantes nas decisões de investimento. Ainda, os achados são relevantes para pesquisas da área de finanças e contabilidade que utilizam essa variável para responder a diferentes questões de pesquisa, uma vez que, ao contrário do apontado pela literatura internacional, as evidências sugerem superioridade de previsão dos modelos random walk quando comparados às previsões dos analistas de mercado / The research presents a study regarding the superiority of market analysts in relation to the random walk models in the forecast of future results of Brazilian companies in the short and long term. The traditional literature indicates unrestricted superiority of market analysts on time series models because of the time and information advantages of these agents. However, recent studies in the international literature point to the need for a reassessment of this superiority, indicating that, for certain company characteristics and especially for long-term estimates, there is no superiority of analysts with respect to time series models. Based on these findings, this research advocates that in the case of Brazil, the superiority of analysts is not unrestricted. This paper evaluates the analysts\' forecasts and the random walk models, both simple and with growth, in the short and long term, for Brazilian publicly traded companies during the period from 2010 to 2015. Data was obtained via the Thomson Reuters® platform, in the I/B/E/S® and Thomson Financial®databases. Following the literature, mean-comparison tests (t-test) were used. As a research differential, a panel data analysis was carried out in order to allow a more precise evaluation of the determinants of analysts\' superiority for the case of Brazil. Furthermore, a simple linear regression model was proposed to evaluate the informational content of market analysts\' forecasts and random walk models. The results indicate: i) greater accuracy of prediction for the simple random walk models, when compared to the random walk models with growth ii) that for the total sample, we can see a greater accuracy of the forecast of random walk models in the short and long term, with analyst superiority only for forecasts with a 3-month lag; (iii) in addition to forecast lag, profit variability, analyst size, dispersion of analysts\' estimates, company size, positive or negative result, market index listing and age of the company in the capital market are factors that alter the superiority of the analysts in the case of Brazil; iv) greater informational content of the random walk forecasts for the prediction of future companies\' profits. These results are important for investment decisions. Moreover, the findings are relevant for research in the field of finance and accounting that use this variable to answer different research questions, since, contrary to the international literature, the evidence suggests forecasting superiority of the random walk models when compared to the market analysts\' forecasts.

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<div>In this thesis we study two different types of self-interacting random walks. First, we study excited random walk in a deterministic, identically-piled cookie environment under the constraint that the total drift contained in the cookies at each site is finite. We show that the walk is recurrent when this parameter is between -1 and 1 and transient when it is less than -1 or greater than 1. In the critical case, we show that the walk is recurrent under a mild assumption on the environment. We also construct an environment where the total drift per site is 1 but in which the walk is transient. This behavior was not present in previously-studied excited random walk models.</div><div><br></div><div>Second, we study the "have your cookie and eat it'' random walk proposed by Pinsky, who already proved criteria for determining when the walk is recurrent or transient and when it is ballistic. We establish limiting distributions for both the hitting times and position of the walk in the transient regime which, depending on the environment, can be either stable or Gaussian.</div>

Neste trabalho estudamos um passeio aleatório, unidimensional com ramificação em Z+ em um meio aleatório não identicamente distribuído. Definimos recorrência e transiência para este processo e apresentamos um critério de classificação. / We study a \"supercritical\" branching random walk on Z+ in a one-dimensional non i.i.d. random environment, which considers both the branching mechanism and the step transition. Criteria of (strong) recurrence and transience are presented for this model.

A estimação da estrutura da taxa de juros é relevante por duas razões fundamentais: em primeiro lugar é considerado como um indicador antecipado de política, sendo uma das principais ferramentas para os bancos centrais como instrumento de política monetária; em segundo lugar, através da curva de rendimentos é possível fazer valoração de ativos financeiros. A causa da sua relevância, tanto na área macroeconômica e como no campo financeiro, uma ampla literatura dedicada a estimá-la se desenvolveu. Neste sentido, o objetivo deste documento é a previsão da curva de rendimentos da Colômbia através da metodologia de Spectrum Singular Analysis (SSA) durante o período 2006-2014. Para a previsão são usados parâmetros diários estimados pelo modelo de fatores de Nelson e Siegel (1987). Os resultados indicam ganhos na acurácia preditiva fora da amostra da abordagem de MSSA em relação ao modelo Random Walk e outros benchmarks amplamente usados na literatura, principalmente nos horizontes de previsão mais curtos. Os resultados são estatisticamente significantes. Assim mesmo, observasse que o MSSA se ajusta melhor que os modelos competidores em todos os horizontes para as previsões das menores maturidades. / The estimation of the Yield curve is relevant because of two fundamental reasons: firstly, it is considered an anticipated indicator of economic policies, being one of the principal central banks tools as instrument of monetary policy; secondly, through this estimation it is possible to valuate financial assets. Due to its relevance in the macroeconomics area and the financial field, an extensive literature has been dedicated to its estimation. Concerning that, the goal of this document is to get a prediction of Colombia’s yield curve through the Spectrum Singular Analysis (SSA) from 2006 to 2014. Daily estimated parameters by Nelson and Siegel (1987) factors model are used to obtain the prognostication. Results are statistically significant and indicate gains of the MMSA on the accuracy of previsions out of the sample in relation to the Random Walk competitor model and other benchmarks widely used in literature, mainly on short term previsions. Likewise, we observe that the MSSA method is better adjusted than competitors’ models in all the horizons for the previsions where maturity is lower. / La estimación de la curva de rendimientos es relevante por dos razones fundamentales: en primer lugar es considerado como un indicador anticipado de política económica, siendo una de las principales herramientas para los bancos centrales como instrumento de política monetaria; en segundo lugar, a través de esta es posible realizar valoración de activos financieros. Dada su relevancia tanto en el área macroeconómica como en el campo financiero una amplia literatura ha sido dedicada a su estimación. En este sentido, el objetivo de este documento es la previsión de la curva de rendimientos de Colombia a través de la metodología de Spectrum Singular Analysis (SSA) durante noviembre de 2006 a diciembre de 2014. Para su pronóstico son usados los parámetros diarios estimados por el modelo de factores de Nelson e Siegel (1987). Los resultados son estadísticamente significativos e indican ganancias del método MSSA en la precisión de las previsiones fuera de la muestra principalmente en horizontes de previsión más cortos en relación al Random Walk y otros benchmarks ampliamente usados en la literatura. Así mismo, se observa que el método MSSA se ajusta mejor que los modelos competidores en todos los horizontes para las previsiones donde el vencimiento es menor.

Neste trabalho estudamos um passeio aleatório, unidimensional com ramificação em Z+ em um meio aleatório não identicamente distribuído. Definimos recorrência e transiência para este processo e apresentamos um critério de classificação. / We study a \"supercritical\" branching random walk on Z+ in a one-dimensional non i.i.d. random environment, which considers both the branching mechanism and the step transition. Criteria of (strong) recurrence and transience are presented for this model.

Random walks describe diffusion processes, where movement at every time step is restricted only to neighbouring locations. Classical random walks are constructed using the non-relativistic Laplacian evolution operator and a coin toss instruction. In quantum theory, an alternative is to use the relativistic Dirac operator. That necessarily introduces an internal degree of freedom (chirality), which may be identified with the coin. The resultant walk spreads quadratically faster than the classical one, and can be applied to a variety of graph theoretical problems. We study in detail the problem of spatial search, i.e. finding a marked site on a hypercubic lattice in d-dimensions. For d=1, the scaling behaviour of classical and quantum spatial search is the same due to the restriction on movement. On the other hand, the restriction on movement hardly matters for d ≥ 3, and scaling behaviour close to Grover’s optimal algorithm(which has no restriction on movement) can be achieved. d=2 is the borderline critical dimension, where infrared divergence in propagation leads to logarithmic slow down that can be minimised using clever chirality flips. In support of these analytic expectations, we present numerical simulation results for d=2 to d=9, using a lattice implementation of the Dirac operator inspired by staggered fermions. We optimise the parameters of the algorithm, and the simulation results demonstrate that the number of binary oracle calls required for d= 2 and d ≥ 3 spatial search problems are O(√NlogN) and O(√N) respectively. Moreover, with increasing d, the results approach the optimal behaviour of Grover’s algorithm(corresponding to mean field theory or d → ∞ limit). In particular, the d = 3 scaling behaviour is only about 25% higher than the optimal value.

ABSTRACT DETERMINATION OF STOCHASTIC MODEL PARAMETERS OF INERTIAL SENSORS &Uuml / nver, Alper PhD, Department of Electric Electronic Engineering Supervisor: Prof. Dr. M&uuml / beccel Demirekler January 2013, 82 pages Gyro and accelerometer systematic errors due to biases, scale factors, and misalignments can be compensated via an on-board Kalman filtering approach in a Navigation System. On the other hand, sensor random noise sources such as Quantization Noise (QN), Angular Random Walk (ARW), Flicker Noise (FN), and Rate Random Walk (RRW) are not easily estimated by an on-board filter, due to their random characteristics. In this thesis a new method based on the variance of difference sequences is proposed to compute the powers of the above mentioned noise sources. The method is capable of online or offline estimation of stochastic model parameters of the inertial sensors. Our aim in this study is the estimation of ARW, FN and RRW parameters besides the quantization and the Gauss-Markov noise parameters of the inertial sensors. The proposed method is tested both on the simulated and the real sensor data and the results are compared with the Allan variance method. Comparison shows very satisfactory results for the performance of the method. Computational load of the new method is less than the computational load of the Allan variance on the order of tens. One of the usages of this method is the individual noise characterization. A noise, whose power spectral density has a constant slope, can be identified accurately by the proposed method. In addition to this, the parameters of the GM noise can also be determined. Another idea developed here is to approximate the overall error source as a combination of ARW and some number of GM sources only. The reasons of selecting such a structure is the feasibility of using these models in a Kalman filter framework for error propagation as well as their generality of modeling other noise sources.