Submitted by Neusa Fagundes (neusa.fagundes@unioeste.br) on 2018-06-18T14:36:28Z No. of bitstreams: 2 Daniela_Nava2018.pdf: 3424820 bytes, checksum: 89e78787f114c44f669182c6285080ae (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-06-18T14:36:28Z (GMT). No. of bitstreams: 2 Daniela_Nava2018.pdf: 3424820 bytes, checksum: 89e78787f114c44f669182c6285080ae (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2018-02-02 / This tesis aimed at studying spatial discrete distributions based on two different points of view, that are, spatial point processes and spatial correlated binomial distribution. The data set came from an experiment setted in an agricultural commercial area in Cascavel city Paraná State, cropped with corn. The experimental area was subdivided into 40 georeferenced patch of land and the number of plants infected by Spodoptera frugiperda was observed within each patch of land. Thus, it is assumed that the data set have a binomial distribution. A study of first order local influence was proposed in order to verify possible influential points. The results suggest that the presence of influential observations in the data set have changed the statistical inference, the predicted values and the respective maps. In a second study, our interest was the spatial distribution of the fall armyworm in the experimental area. In order to do that, we used spatial point processes, where each plant infected by the insect within the experimental area was considered as an event of interest. An anisotropy study was carried out using different point process techniques, such as K directional function and wavelet test. The results show that the spatial distribution of the fall armyworm follow a Poisson cluster process with an evident anisotropy, mainly due to the shape of the experimental area. / O objetivo deste trabalho foi discutir distribuições discretas espaciais utilizando pontos de vista distintos, a saber, processos pontuais espaciais e distribuição binomial para dados espacialmente correlacionados. Os dados utilizados são provenientes de um experimento agrícola implantado em uma área comercial agrícola no município de Cascavel, estado do Paraná, cultivada com a cultura do milho. Subdividiu-se a área experimental em 40 parcelas georeferenciadas e observou-se o número de plantas atacadas pela lagarta do cartucho, do total de plantas de cada parcela. Para tal, assumiu-se que os dados possuem distribuição binomial. Propôs-se um estudo de análise de influência local de primeira ordem com o interesse em verificar possíveis pontos influentes. Os resultados obtidos sugerem que a presença de observações influentes nos dados modificam a inferência estatística, os valores preditos e os respectivos mapas. Em um segundo estudo, que teve como interesse a distribuição espacial da lagarta do cartucho na área experimental, utilizou-se de ferramentais de estatística espacial pontual. Para tal, cada planta infectada pelo inseto dentro da área experimental foi considerada como um evento de interesse. Realizou-se um estudo de anisotropia a partir de diferentes técnicas de processos pontuais, como K direcional e teste de ondaletas. Os resultados mostraram que a distribuição espacial da lagarta segue um processo pontual de Poisson agrupado com evidente anisotropia principalmente devido à forma da área experimental.

Metodologias para obtenção do tamanho amostral para estimar a concentração de organismos em água de lastro e verificar normas internacionais são desenvolvidas sob uma abordagem bayesiana. Consideramos os critérios da cobertura média, do tamanho médio e da minimização do custo total sob os modelos Poisson com distribuição a priori gama e binomial negativo com distribuição a priori Pearson Tipo VI. Além disso, consideramos um processo Dirichlet como distribuição a priori no modelo Poisson com o propósito de obter maior flexibilidade e robustez. Para fins de aplicação, implementamos rotinas computacionais usando a linguagem R. / Sample size methodologies for estimating the organism concentration in ballast water and for verifying international standards are developed under a Bayesian approach. We consider the criteria of average coverage, of average length and of total cost minimization under the Poisson model with a gamma prior distribution and the negative binomial model with a Pearson type VI prior distribution. Furthermore, we consider a Dirichlet process as a prior distribution in the Poisson model with the purpose to gain more flexibility and robustness. For practical applications, we implemented computational routines using the R language.

Pas de résumé en français / Malaria is a devastating global health problem that affected 219 million people and caused 660,000 deaths in 2010. Inaccurate estimation of the level of infection may have adverse clinical and therapeutic implications for patients, and for epidemiological endpoint measurements. The level of infection, expressed as the parasite density (PD), is classically defined as the number of asexual parasites relative to a microliter of blood. Microscopy of Giemsa-stained thick blood smears (TBSs) is the gold standard for parasite enumeration. Parasites are counted in a predetermined number of high-power fields (HPFs) or against a fixed number of leukocytes. PD estimation methods usually involve threshold values; either the number of leukocytes counted or the number of HPFs read. Most of these methods assume that (1) the distribution of the thickness of the TBS, and hence the distribution of parasites and leukocytes within the TBS, is homogeneous; and that (2) parasites and leukocytes are evenly distributed in TBSs, and thus can be modeled through a Poisson-distribution. The violation of these assumptions commonly results in overdispersion. Firstly, we studied the statistical properties (mean error, coefficient of variation, false negative rates) of PD estimators of commonly used threshold-based counting techniques and assessed the influence of the thresholds on the cost-effectiveness of these methods. Secondly, we constituted and published the first dataset on parasite and leukocyte counts per HPF. Two sources of overdispersion in data were investigated: latent heterogeneity and spatial dependence. We accounted for unobserved heterogeneity in data by considering more flexible models that allow for overdispersion. Of particular interest were the negative binomial model (NB) and mixture models. The dependent structure in data was modeled with hidden Markov models (HMMs). We found evidence that assumptions (1) and (2) are inconsistent with parasite and leukocyte distributions. The NB-HMM is the closest model to the unknown distribution that generates the data. Finally, we devised a reduced reading procedure of the PD that aims to a better operational optimization and a practical assessing of the heterogeneity in the distribution of parasites and leukocytes in TBSs. A patent application process has been launched and a prototype development of the counter is in process.

Quality, as well as stability of processes check is nowadays gaining on its significance. The main driving force of its increasing importance is the rapid expansion of series production. Large-scale manufacturing processes are concerned, in terms of the number of operators, direct and indirect influence on rejects, but also on process stability. There are several quality characteristics, defined by utility properties, that can be easily measurable (linear dimensions, solidity, elongation, humidity, concentration) or directly immeasurable, mostly subjective (fragrance, taste, color, comfort while using, appearance). Statistical Process Control-SPC features the preventive tool of quality control, because based on the early detection of significant divergences of the process from the predetermined level, it is possible to execute interventions in the process with the aim of maintaining the acceptable and stable level and improving the process. This manufacturing process check will be the topic of my thesis. At first, Shewhart's control charts analysis will be done to determine strong process instability. Consequently, analysis will be carried out in test chi-square, used to determine the influence of each factor on the process of stability (operators, type of shift, type of product, type of defect on the product). All the practical part will be processed in statistical software MINITAB15. The thesis will be complemented by the findings from the examination of the features of interval estimates of parameter p for binomial distribution - numeric stability in the various statistical software (specifically Minitab 15, Statistica, Matlab 7.8.0). Master's thesis was supported by project from MSMT of the Czech Republic no. 1M06047 Center for Quality and Reliability of Production.

The premise of this report is to delve into sports betting and whether favourable opportunities can be found, more specifically focusing on over and under odds for number of goals scored in football games of the Premier League. Using historical data from football matches several models are developed, the characteristics of goals warranting the use of probability based Poisson and Negative Binomial models, as well as Bayesian Poisson regression for goal predictions. Once these models were developed odds was found and compared to bookmakers, the results indicated that all models, to varying degrees, find favourable opportunities and profitable betting strategies can be identified. This suggests that bookmakers do not always price betting products according to their true probabilities likely due to book balancing and informational asymmetries. Furthermore it indicates that there is a presence of inefficiencies in the sports betting market. / Den här rapporten kommer djupdyka i betting och huruvida gynnsamma möjligheter kan hittas. Mer specifikt kommer ett fokus ligga på över/under odds för antalet mål i fotbollsmatcher i engelska Premier League. Genom att använda historisk data från fotbollsmatcher utvecklas flera olika statistiska modeller för att förutspå antalet mål i fotbollsmatcher. Skattning av Poisson och Negativ Binomial fördelningar samt utvecklandet av en Bayesiansk Poisson regressionsmodell motiveras av egenskaperna hos antalet mål i fotbollsmatcher. Med dessa modeller, beräknas odds för flera framtida matcher inom Premier League och dessa jämfördes med odds som ges av bettingbolag. Resultaten indikerar att alla modeller kan, i olika stor utsträckning, hitta gynnsamma möjligheter och lönsamma betting strategier kan identifieras. Detta tyder på att bettingbolag inte alltid sätter sina odds enbart baserat på den faktiska sannolikheten, vilket troligtvis beror på att bolagen balanserar sina böcker samt informationsasymmetrier. Dessutom indikerar resultatet på att det finns faktorer på bettingmarknaden som gör marknaden ineffektiv.

In this paper, we first present the basic principles of set theory and combinatorial analysis which are the most useful tools in computing probabilities. Then, we show some important properties derived from axioms of probability. Conditional probabilities come into play not only when some partial information is available, but also as a tool to compute probabilities more easily, even when partial information is unavailable. Then, the concept of random variable and its some related properties are introduced. For univariate random variables, we introduce the basic properties of some common discrete and continuous distributions. The important properties of jointly distributed random variables are also considered. Some inequalities, the law of large numbers and the central limit theorem are discussed. Finally, we introduce additional topics the Poisson process.

The Theses deals with applications of mathematical knowledge in teaching biology and it is divided into four chapters. Each chapter is dedicated to another application: 1. Application of conditional probability in medical diagnostics, 2. Application of exponential function in population ecology, 3. Application of logic functions in mathematical modelation of neuron and 4. Aplication of binomial theorem and binomial distribution in genetics. Each application contains solved problems, a worksheet for students and a solution for each worksheet. Two application (1. and 2.) have been tested in teaching and as an assessment of my lessons students filled questionnaires. Results of these questionnaires are processed in the end of these chapters. This Thesis can be used in teaching or self-studying.

Θεωρούμε μια ακολουθία από n δυαδικά πειράματα. Ροή επιτυχιών μήκους k είναι μια ακολουθία από k συνεχόμενες επιτυχίες οι οποίες έπονται και ακολουθούνται από αποτυχίες ή τίποτα. Στην εργασία αυτή αρχικά μελετάται η τυχαία μεταβλητή Ν(n,k) η οποία παριστάνει τον αριθμό των ροών επιτυχιών μήκους k σε n δυαδικά πειράματα. Προσδιορίζεται η ακριβής κατανομή μέσω συνδιαστικών μεθόδων, αναδρομικών σχέσεων και μέσω της μεθόδου εμβάπτισης τυχαίας μεταβλητής σε Μαρκοβιανή αλυσίδα. Η μελέτη γίνεται για ανεξάρτητες και ισόνομες και για ανεξάρτητες όχι κατ’ ανάγκην ισόνομες δυαδικές ακολουθίες. Μελετάται επίσης η τυχαία μεταβλητή M(n,k)η οποία παριστάνει τον αριθμό των ροών επιτυχιών τουλάχιστον k σε n δυαδικά πειράματα. Ένα συνεχόμενο-k -από-τα-n:F σύστημα αποτυχίας είναι ένα σύστημα n συνιστωσών το οποίο αποτυγχάνει αν και μόνο αν αποτύχουν τουλάχιστον k συνεχόμενες συνιστώσες του. Τα συνεχόμενα-k-από-τα-n:F συστήματα αποτυχίας έχουν προταθεί ως κατάλληλα πρότυπα για συστήματα μεταφοράς πετρελαίου, τηλεπικοινωνιακά συστήματα κ.α. Ένα m-συνεχόμενο-k-από-τα-n:F σύστημα αποτυχίας είναι ένα σύστημα n συνιστωσών το οποίο αποτυγχάνει αν και μόνο αν υπάρχουν τουλάχιστον m ροές από k συνεχόμενες αποτυχημένες συνιστώσες του. Μελετάται η σχέση της αξιοπιστίας των ανωτέρω συστημάτων με τη συνάρτηση πιθανότητας και τη συνάρτηση κατανομής της τυχαίας μεταβλητής N(n,k). Αναπτύσσονται οι μέθοδοι που έχουν δοθεί για τον προσδιορισμό της αξιοπιστίας τους και δίνονται ακριβείς εκφράσεις της μέσω πολυωνυμικών συντελεστών, διωνυμικών συντελεστών, αναδρομικών σχέσεων και της μεθόδου εμβάπτισης σε Μαρκοβιανή αλυσίδα. Η μελέτη γίνεται για συστήματα με ανεξάρτητες συνιστώσες, γαι συστήματα με ομογενή Μαρκοβιανή εξάρτηση ενός βήματος και για συστήματα με Μαρκοβιανά εξαρτημένες συνιστώσες (k-1) βημάτων. Τέλος παρουσιάζονται αριθμητικά παραδείγματα για περαιτέρω διευκρίνηση και σύγκριση των μεθόδων υπολογισμού της κατανομής της N(n,k) και της αξιοπιστίας των ανωτέρω συστημάτων αποτυχιών. / Consider a sequence of n two state (success-failure) trials. A success run of length k is a sequence of k consecutive successes proceeded and succeeded by failures or nothing. In this thesis the random variable N(n,k) denoting the number of success runs of length k in n binary trials is studied. The exact distribution of N(n,k) is given, via combinatorial analysis, recursive relations and using the Markov chain imbedding technique. The study is carried out for independent but not identically distributed binary sequences. Further, the random variable M(n,k)denoting the number of success runs of length at least k in n binary trials is also studied. A consecutive-k-out-of-n : F system is a system which consists of n components ordered on a line, which fails if and only if at least k consecutive components fail. Such systems have been used to model telecommunication, oil pipeline systems e.t.c. An m-consecutive-k -out-of-n : F system consists of n components ordered on a line, which fails if and only if there are at least m non-overlapping runs of k consecutive failed components. The reliability of the above mentioned systems is related to the cumulative distribution function of the random variable N(n,k) . Exact formulae for the reliability is given by means of binomial and multinomial coefficients, via recursive relations and using the Markov chain imbedding technique. The study is accomplished for systems with independent and Markov dependent components. Finally, numerical examples are given for comparison of the various used methods and to illustrate the theoretical results.

Malaria is a devastating global health problem that affected 219 million people and caused 660,000 deaths in 2010. Inaccurate estimation of the level of infection may have adverse clinical and therapeutic implications for patients, and for epidemiological endpoint measurements. The level of infection, expressed as the parasite density (PD), is classically defined as the number of asexual parasites relative to a microliter of blood. Microscopy of Giemsa-stained thick blood smears (TBSs) is the gold standard for parasite enumeration. Parasites are counted in a predetermined number of high-power fields (HPFs) or against a fixed number of leukocytes. PD estimation methods usually involve threshold values; either the number of leukocytes counted or the number of HPFs read. Most of these methods assume that (1) the distribution of the thickness of the TBS, and hence the distribution of parasites and leukocytes within the TBS, is homogeneous; and that (2) parasites and leukocytes are evenly distributed in TBSs, and thus can be modeled through a Poisson-distribution. The violation of these assumptions commonly results in overdispersion. Firstly, we studied the statistical properties (mean error, coefficient of variation, false negative rates) of PD estimators of commonly used threshold-based counting techniques and assessed the influence of the thresholds on the cost-effectiveness of these methods. Secondly, we constituted and published the first dataset on parasite and leukocyte counts per HPF. Two sources of overdispersion in data were investigated: latent heterogeneity and spatial dependence. We accounted for unobserved heterogeneity in data by considering more flexible models that allow for overdispersion. Of particular interest were the negative binomial model (NB) and mixture models. The dependent structure in data was modeled with hidden Markov models (HMMs). We found evidence that assumptions (1) and (2) are inconsistent with parasite and leukocyte distributions. The NB-HMM is the closest model to the unknown distribution that generates the data. Finally, we devised a reduced reading procedure of the PD that aims to a better operational optimization and a practical assessing of the heterogeneity in the distribution of parasites and leukocytes in TBSs. A patent application process has been launched and a prototype development of the counter is in process.

This thesis is divided into three main parts. In the first, we discuss that, although permutation tests can provide exact control of false positives under the reasonable assumption of exchangeability, there are common examples in which global exchangeability does not hold, such as in experiments with repeated measurements or tests in which subjects are related to each other. To allow permutation inference in such cases, we propose an extension of the well known concept of exchangeability blocks, allowing these to be nested in a hierarchical, multi-level definition. This definition allows permutations that retain the original joint distribution unaltered, thus preserving exchangeability. The null hypothesis is tested using only a subset of all otherwise possible permutations. We do not need to explicitly model the degree of dependence between observations; rather the use of such permutation scheme leaves any dependence intact. The strategy is compatible with heteroscedasticity and can be used with permutations, sign flippings, or both combined. In the second part, we exploit properties of test statistics to obtain accelerations irrespective of generic software or hardware improvements. We compare six different approaches using synthetic and real data, assessing the methods in terms of their error rates, power, agreement with a reference result, and the risk of taking a different decision regarding the rejection of the null hypotheses (known as the resampling risk). In the third part, we investigate and compare the different methods for assessment of cortical volume and area from magnetic resonance images using surface-based methods. Using data from young adults born with very low birth weight and coetaneous controls, we show that instead of volume, the permutation-based non-parametric combination (NPC) of thickness and area is a more sensitive option for studying joint effects on these two quantities, giving equal weight to variation in both, and allowing a better characterisation of biological processes that can affect brain morphology.