Στην εργασία αυτή παρουσιάζεται η πιθανογεννήτρια του αριθμού των απογόνων της ν-oστης γενιάς μια κλαδωτής ανέλιξης ως το πηλίκο των πιθανογεννήτριων δύο γεωμετρικών κατανομών. Στην βιβλιογραφία, με εξαίρεση δύο συγκεκριμένες περιπτώσεις (πηλίκα πιθανογεννητριών αρνητικής διωνυμικής με γεωμετρική, Kemp, 1979, και γεωμετρικής με Poisson Jayasree and Swamy, 2006), δεν έχει μελετηθεί το γενικότερο πρόβλημα των συνθηκών που επιτρέπουν το πηλίκο δύο πιθανογεννητριών να είναι η πιθανογεννήτρια μιας διακριτής μη αρνητικής τυχαίας μεταβλητής. Εδώ δίνονται οι ικανές και αναγκαίες συνθήκες για τα αντίστοιχα πηλίκα πιθανογεννητριών κατανομών από την οικογένεια Katz ή την οικογένεια Sundt and Jewell με την γεωμετρική κατανομή. Μελετάται επίσης και το πηλίκο απείρως διαιρετών κατανομών με την Poisson και παρουσιάζονται αναλυτικά τέτοια παραδείγματα. Διάφορες ιδιότητες των κατανομών που προκύπτουν εξετάζονται και γίνεται εκτίμηση των παραμέτρων. Στη συνέχεια, παρουσίαζεται μια διδιάστατη κλαδωτή ανέλιξη, δίνεται αναλυτικός τύπος για την πιθανογεννήτρια της από κοινού συνάρτησης κατανομής του πλήθους των δύο ειδών απογόνων της ν-oστης γενιάς, και αποδεικνύεται ότι αυτή μπορεί να γραφεί ως το πηλίκο των πιθανογεννήτριων δύο διδιαστάτων γεωμετρικών κατανομών. Μελετούμε γενικότερα το αντίστοιχο πρόβλημα για διδιάστατες τ.μ. και εξετάζουμε τις ικανές συνθήκες στις περιπτώσεις πηλίκου πιθανογεννητριών της διδιάστατης αρνητικής διωνυμικής με τη διδιάστατη γεωμετρική και της διδιάστατης αρνητικής διωνυμικής με τη διδιάστατη Poisson. Παρουσιάζονται αναγωγικές και αναλυτικές σχέσεις για τις πιθανότητες και τις παραγοντικές ροπές και μελετάται η μορφή των πιθανογεννητριών τόσο των περιθωρίων όσο και των δεσμευμένων κατανομών που προκύπτουν. / In this master thesis we observe, that the probability generating function of the number of the descendants of the n-th generation in a branching process, can be represented as the ratio of the probability generating functions (p.g.f.) of two geometric distributions. In the literature, with the exception of two particular cases (ratio of negative binomial with geometric, Kemp, 1979, and geometric with Poisson, Jayasree and Swamy, 2006), the general problem, for the conditions that allow the ratio of two p.g.f.’s to be the p.g.f. of a discrete non-negative random variable (r.v.), has not been considered. Here, are given the necessary and sufficient conditions for the ratios of the p.g.f. of a distribution from the Katz or the Sundt and Jewell family with the p.g.f. of a Geometric distribution. The ratio of an infinitely divisible r.v. with a Poisson r.v. is also studied and various such examples are presented in detail. Properties of these distributions are given and also parameters estimators are provided. In the sequel, a bivariate branching process is considered and the explicit form for the p.g.f. of the number of two type descendants in the n-th generation is derived. It is proved, that it can be written as the ratio of the p.g.f.’s of two bivariate geometric distributions. The sufficient conditions in the cases of the ratio of the bivariate negative binomial distribution with the bivariate geometric distribution and the bivariate negative binomial distribution with the bivariate Poisson distribution are examined. Recurrence relations and the explicit form of the probabilities and the factorial moments are given and the form of the p.g.f.’s for the marginals and the conditional distributions are studied.

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Kim, Straub, and Keyes introduced the statistical temperature molecular dynamics (STMD) algorithm to overcome broken ergodicity by sampling a non­-Boltzmann flat energy histogram as noted in Kim, Straub, and Keyes, Phys. Rev. Lett. 97: 050601 (2007). Canonical averages are calculated via reweighting to the desired temperature. While STMD is promising, its application has been almost entirely to simple or model systems. In this dissertation the implementation of STMD into the biosimulation package CHARMM is used to simulate the methionine enkephalin pentamer peptide with a methione terminal cap in a droplet of CHARMM TIP3P water molecules. Chain thermodynamics is analyzed from the novel perspective of the statistical temperature as a function of potential energy, $TS(U), automatically generated by STMD. Both the minimum in the slope of $TS(U), and the peak in the heat capacity as a function of temperature, calculated via reweighting, indicate a collapse transition at Tθ ≈ 253K. Distributions of dihedral angles are obtained as a function of temperature. Rotamer regions found in the literature are reproduced, along with unique regions not found previously, including with advanced algorithms, indicating the power of STMD enhanced sampling.

Resumo: O psilídeo Diaphorina citri Kuwayama tornou-se nos últimos anos, uma das mais importantes pragas na cultura de citros, principalmente pelos prejuízos causados às plantas devido à transmissão da bactéria causadora da doença Huanglongbing (HLB) ou Greening. Com a finalidade de estudar a distribuição espacial de ninfas e adultos desta praga, instalou-se um experimento em 2 áreas de citros com histórico de ocorrência de HLB, no município de Matão, região central do Estado de São Paulo, uma com plantas de 4 anos e outra com plantas de 12 anos de idade. Para estudo da agregação da população nas plantas, foram utilizados os seguintes índices de dispersão: razão variância/média (I), índice de Morisita (Id), coeficiente de Green (Cx) e expoente k da distribuição binomial negativa para cada amostragem. A distribuição binomial negativa foi o modelo mais adequado para representar a distribuição espacial do psilídeo na cultura de citros, tanto para ninfas como para adultos. Através da análise destes índices, verificou-se que, na maioria das amostragens, as ninfas encontradas nas brotações e os adultos capturados nas armadilhas apresentaram distribuição agregada. Foram desenvolvidos planos de amostragem seqüencial para ninfas e adultos em região com e sem HLB, e os números máximos de amostras esperados para se tomar a decisão foram de 264 e 83 para ninfas, em regiões com e sem a doença, e de 184 e 150 amostras para adultos, em regiões com e sem a doença. / Abstract: The psyllid Diaphorina citri Kuwayama is one of the most important pests of citrus, mostly because of plant damage due to transmission of the bacterium that causes Huanglongbing (HLB) or Greening disease. The experiment was carried out in 2 sweet orange orchards with previous HLB occurrence in Matão (central region of the State of São Paulo, Brazil), in plants with 4 and 12 years of age, in order to study the spatial distribution of nymphs and adults of this pest. The following dispersion indices were used to study pest aggregation in the citrus plants: variance/mean relationship (I), index of Morisita (Id), coefficient of Green (Cx), and the k exponent of negative binomial distribution for each sampling. The negative binomial distribution was the most representative spatial distribution of this psyllid in citrus, for both nymphs and adults. The analysis of these indices showed that, for most samplings, psyllid nymphs found in branches and adults caught in traps presented an aggregated distribution. Sequential sampling plans were developed for nymphs and adults in regions with and without HLB, and the maximum number of samples for decision making was 264 and 83 samples for nymphs in regions with and without the disease, and, 184 and 150 samples for adults, in regions with and without the disease, respectively. / Orientador: José Carlos Barbosa / Coorientador: Pedro Takao Yamamoto / Banca: Odair Aparecido Fernandes / Banca: Wilson Itamar Maruyama / Banca: Antonio Baldo Geraldo Martins / Banca: Eduardo Sanches Stuchi / Doutor

Parton distribution functions (PDFs) provide a description of the quark and gluon content of the proton. They are important input into theoretical calculations of hadronic observables, and are obtained by fitting to a wide range of experimental data. The NNPDF approach to fitting PDFs provides a robust and reliable determination of their central values and uncertainties. The PDFs are modelled using neural networks, while the uncertainties are generated through the use of Monte Carlo replica datasets. In this thesis I provide an in depth description of development of the latest NNPDF determination: NNPDF3.0. A number of novel adaptations to the genetic algorithm and network structure are outlined and the results of tests as to their effectiveness are shown. Centrally, the use of closure tests, where artificial data is generated according to a known theory and used to perform a fit, has been instrumental in both the development and validation of the NNPDF3.0 approach. The results of these tests, which demonstrate the ability of our methodology to reproduce a known underlying law, are investigated in detail. Finally, results from the NNPDF3.0 PDF sets are presented. The parton distributions obtained are compared with results from other PDF collaborations, and PDFs fit to limited datasets are also discussed. Physical observables relevant for future collider runs are presented and compared to other determinations.

This thesis challenges several concepts in finance. Firstly, it is the Markowitz's solution to the portfolio problem. It introduces a new method which de- noises the covariance matrix - the cornerstone of the portfolio management. Random Matrix Theory originates in particle physics and was recently intro- duced to finance as the intersection between economics and natural sciences has widened over the past couple of years. Often discussed Efficient Market Hypothesis is opposed by adopting the assumption, that financial returns are driven by Paretian distributions, in- stead of Gaussian ones, as conjured by Mandelbrot some 50 years ago. The portfolio selection is set in a framework, where Expected Shortfall replaces the standard deviation as the risk measure. Therefore, direct optimi- sation of the portfolio is implemented to be compared with the performance of the classical solution and its denoised counterpart. The results are evalu- ated in a controlled environment of Monte Carlo simulation as well as using empirical data from S&P 500 constituents. 1

Nous nous intéressons à la fois à la modélisation des fréquences des mots dans les collections textuelles et aux modèles probabilistes de recherche d'information (RI). Concernant les modèles statistiques de fréquences de mots, nous portons notre attention sur l'étude du phénomène de rafale (burstiness). Nous établissons une propriété sur les distributions de probabilité caractérisant leur capacité à modéliser ce phénomène et nous étudions ensuite les distributions Beta Negative Binomial et Log-Logistique pour la modélisation des fréquences de mots. Nous portons ensuite notre attention sur les modèles probabilistes de RI et leur propriétés fondamentales. Nous pouvons montrer que les modèles classiques ne reposent pas sur des lois de probabilité en rafale, même si des propriétés fondamentales comme la concavité des modèles permettent implicitement de le prendre en compte. Nous introduisons ensuite une nouvelle famille de modèles probabiliste pour la recherche d'information, fondé sur la notion d'information de Shannon et qui permet d'établir un lien conséquent entre les propriétés importantes des modèles de RI et le phénomène de rafale. Enfin, nous étudions empiriquement et théoriquement les modèles de rétro-pertinence. Nous proposons un cadre théorique qui permet ainsi d'expliquer leurs caractéristiques empiriques et leur performances. Ceci permet entre autres de mettre en avant les propriétés importantes des modèles de retro-pertinence et de montrer que certains modèles de référence sont déficients. / The present study deals with word frequencies distributions and their relation to probabilistic Information Retrieval (IR) models. We examine the burstiness phenomenon of word frequencies in textual collections. We propose to model this phenomenon as a property of probability distributions and we study the Beta Negative Binomial and Log-Logistic distributions to model word frequencies. We then focus on probabilistic IR models and their fundamental properties. Our analysis reveals that probability distributions underlying most state-of-the-art models do not take this phenomenon into account , even if fundamental properties of IR models such as concavity enable implicitly to take it into account. We then introduce a novel family of probabilistic IR model, based on Shannon information. These new models bridge the gap between significant properties of IR models and the burstiness phenomenon of word frequencies. Lastly, we study empirically and theoretically pseudo relevance feedback models. We propose a theoretical framework which explain well the empirical behaviour and performance of pseudo relevance feedback models. Overall, this highlights interesting properties for pseudo relevance feedback and shows that some state-of-the-art model are inadequate.

Recentemente, Cordeiro e de Castro (2011) apresentaram uma classe generalizada baseada na distribuição Kumaraswamy (Kw-G). Essa classe de distribuições modela as formas de risco crescente, decrescente, unimodal e forma de U ou de banheira. Uma importante distribuição pertencente a essa classe é a distribuição Kumaraswamy Weibull modificada (KwMW) proposta por Cordeiro; Ortega e Silva (2013). Com isso foi utilizada essa distribuição para o desenvolvimento de algumas novas propriedades e análise bayesiana. Além disso, foi desenvolvida uma nova distribuição de probabilidade a partir da distribuição gama generalizada geométrica (GGG) que foi denominada de gama generalizada geométrica exponenciada (GGGE). Para a nova distribuição GGGE foram calculados os momentos, a função geradora de momentos, os desvios médios, a confiabilidade e as estatísticas de ordem. Desenvolveu-se o modelo de regressão log-gama generalizada geométrica exponenciada. Para a estimação dos parâmetros, foram utilizados os métodos de máxima verossimilhança e bayesiano e, finalmente, para ilustrar a aplicação da nova distribuição foi analisado um conjunto de dados reais. / Recently, Cordeiro and de Castro (2011) showed a generalized class based on the Kumaraswamy distribution (Kw-G). This class of models has crescent risk forms, decrescent, unimodal and U or bathtub form. An important distribution belonging to this class the Kumaraswamy modified Weibull distribution (KwMW), proposed by Cordeiro; Ortega e Silva (2013). Thus this distribution was used to develop some new properties and bayesian analysis. Furthermore, we develop a new probability distribution from the generalized gamma geometric distribution (GGG) which it is called generalized gamma geometric exponentiated (GGGE) distribution. For the new distribution we calculate the moments, moment generating function, mean deviation, reliability and order statistics. We define a log-generalized gamma geometric exponentiated regression model. The methods used to estimate the model parameters are: maximum likelihood and bayesian. Finally, we illustrate the potentiality of the new distribution by means of an application to a real data set.

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