Made available in DSpace on 2016-06-02T20:06:07Z (GMT). No. of bitstreams: 1 4375.pdf: 903031 bytes, checksum: 03118f406867a5d7be3cbc63571d4a2b (MD5) Previous issue date: 2012-04-12 / Financiadora de Estudos e Projetos / The chemical induction of carcinogens in chemopreventive animal experiments is becoming increasingly frequent in biological research. The purpose of these biological experiments is to evaluate the effect of a particular treatment on the rate of tumors incidence in animals. In this work, the number of promoted tumors per animal will be parametrically modeled following the suggestions given by Kokoska (1987) and Freedman et al. (1993). The study of these chemopreventive experiments will be presented in the context of the destructive model proposed by Rodrigues et al. (2010) with terminal variable that allows or censures the experiment at time of the animal death. Since the data analyzed in this field are subject to excess of zeros (Freedman et al. (1993)), we propose for the number of promoted tumors a negative binomial distribution (NB), a zero-inflated Poisson distribution (ZIP), and a zero-inflated Negative Binomial distribution (ZINB). The selection of these models will be made through the likelihood ratio test and the AIC, BIC criteria. The estimation of its parameters will be obtained by using the method of maximum likelihood, and further simulation studies will also be realized. As a future proposition to finalize this project, it is suggested the Bayesian methodology as an alternative to the method of maximum likelihood via the EM algorithm. / A indução química de substâncias cancerígenas em experimentos quimiopreventivos em animais é cada vez mais frequente em pesquisas biológicas. O objetivo destes experimentos biológicos é avaliar o efeito de um determinado tratamento na taxa de incidência de tumores em animais. Neste trabalho o número de tumores promovidos por animal será modelado parametricamente seguindo as sugestões dadas por Kokoska (1987) e por Freedman et al. (1993). O estudo desses experimentos quimiopreventivos será apresentado no contexto do modelo destrutivo proposto por Rodrigues et al. (2010) com variável terminal que condiciona ou censura o experimento no instante de morte do animal. Os dados analisados possuem uma grande quantidade de zeros, portanto será proposto para o número de tumores promovidos as seguintes distribuições: binomial negativa, a distribuição de Poisson com zeros inflacionados e a distribuição binomial negativa com zeros inflacionados. A seleção destes modelos será feita através do teste da razão de verossimilhança e os critérios AIC, BIC. As estimativas dos respectivos parâmetros serão obtidas utilizando o método de máxima verossimilhança e serão feitos estudos de simulação. Para continuar este projeto, a proposta futura é utilizar a metodologia Bayesiana como alternativa ao método de máxima verossimilhança via algoritmo EM.

Les données comptées (count data) possèdent des distributions ayant des caractéristiques particulières comme la non-normalité, l’hétérogénéité des variances ainsi qu’un nombre important de zéros. Il est donc nécessaire d’utiliser les modèles appropriés afin d’obtenir des résultats non biaisés. Ce mémoire compare quatre modèles d’analyse pouvant être utilisés pour les données comptées : le modèle de Poisson, le modèle binomial négatif, le modèle de Poisson avec inflation du zéro et le modèle binomial négatif avec inflation du zéro. À des fins de comparaisons, la prédiction de la proportion du zéro, la confirmation ou l’infirmation des différentes hypothèses ainsi que la prédiction des moyennes furent utilisées afin de déterminer l’adéquation des différents modèles. Pour ce faire, le nombre d’arrestations des membres de gangs de rue sur le territoire de Montréal fut utilisé pour la période de 2005 à 2007. L’échantillon est composé de 470 hommes, âgés de 18 à 59 ans. Au terme des analyses, le modèle le plus adéquat est le modèle binomial négatif puisque celui-ci produit des résultats significatifs, s’adapte bien aux données observées et produit une proportion de zéro très similaire à celle observée. / Count data have distributions with specific characteristics such as non-normality, heterogeneity of variances and a large number of zeros. It is necessary to use appropriate models to obtain unbiased results. This memoir compares four models of analysis that can be used for count data: the Poisson model, the negative binomial model, the Poisson model with zero inflation and the negative binomial model with zero inflation. For purposes of comparison, the prediction of the proportion of zero, the confirmation or refutation of the various assumptions and the prediction of average number of arrrests were used to determine the adequacy of the different models. To do this, the number of arrests of members of street gangs in the Montreal area was used for the period 2005 to 2007. The sample consisted of 470 men, aged 18 to 59 years. After the analysis, the most suitable model is the negative binomial model since it produced significant results, adapts well to the observed data and produces a zero proportion very similar to that observed.

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.

高解析法是訊號處理上處理離散訊號系統的重要方法，將之運用在有限二項組合及有限卜瓦松組合的參數解上，可以得到很好的結果。本篇論文除了將高解析法在有限二項組合及有限卜瓦松之運用作一探討外，並在有限二項組合的基礎上推論有限負二項組合在特殊情況下的解法。 / High-resolution inversion method is an important technique to solve discrete signal system problems. We can solve finite binomial mixtures and finite Poisson mixture problems with high-resolution inversion method. In thispaper, we shall provide and discuss how the high-resolution inversion method used in finite binomial mixtures and finite Poisson mixture problems.In addition,we shall also extend our methods to solve finite negative binomial mixture problems with some assumptions same as those for finitebinomial mixtures.

This thesis is about the economic aspects of public procurement of services through auctionsin Sweden. It focuses on two different institutions, auctions used to find foste r-parents forboarded out children in the 19th century, and auctions of cleaning service contracts in the 20 thcentury. I n both cases, the contracting entity is the municipality or its representative, thelowest bidder wins the auction, and is paid in accordance with his/her bid.In the child auctions, c hildren were allotted to foster-parents by means of an open biddingprocess, the descending English auction, where the bids were given continuously to theauctioneer. In modern public procurement sealed bids ar e used in accordance with the firstprice,sealed bid auction. The first part of this thesis is about price formation in the childauctions and a study is made of the children who were auctioned several times, indicatingasymmetric information among bidders or adverse selection in this market. These subjects arestudied using field data on 601 child auctions held in Northern Sweden during the period 1863to 1889. The empirical findings in the first paper suggest that the foster-parents had a cleareconomic motive in these auctions. The child characteristics significantly affect the amount ofcompensation paid to the foster-parent. There is also evidence that farmers preferred older,more productive children. The second paper studies whether a re-auctioned child commandeda higher or lower price than a child that was not re-auctioned. The results indicate some formof asymmetric information because foster-parents demanded a higher level of compensationfor a re-auctioned child. The results also suggest that the probability that a child was reauctionedincreased if he/she was not healthy.The third paper in the thesis discusses a kind of "paradox". Although there is a competitiveeffect on the bids in the auction of cleaning service contracts, the contracting entity has anoption, given by law, to restrict the number of bidders. In th is paper, an implementation costis introduced fo r the contracting entity to justify such a restriction. The results, based onSwedish municipality data, indicate that contract and municipality characteristics, assumed toaffect the implementation cost, affect the volume of the procurement, and the number ofbidders, but not necessarily the choice of allocation mechanism. The final paper studiesregional differences in bids, costs, and competition in municipal procurement using the samedata as in paper [3]. The results show higher estimated costs for completing the contract, butlower estimated mean bids in the major city area of Stockholm compared with the res t of thecountry. This is explained by lower profit margins and higher operational costs in the majorcity area. An analysis is also carried out of why the lowest bidder is not always the contractedbidder. / <p>Härtill 4 delar.</p> / digitalisering@umu

Managed lanes are a form of congestion pricing that use occupancy and toll payment requirements to utilize capacity more efficiently. How socio-spatial characteristics impact users’ travel behavior toward managed lanes is the main research question of this study. This research is a case study of the conversion of a High Occupancy Vehicle (HOV) lane to a High Occupancy Toll (HOT) lane, implemented in Atlanta I-85 on 2011. To minimize the cost and maximize the size of the collected data, an innovative and cost-effective modeling framework for socioeconomic analysis of managed lanes has been developed. Instead of surveys, this research is based on the observation of one and a half million license plates, matched to household locations, collected over a two-year study period. Purchased marketing data, which include detailed household socioeconomic characteristics, supplemented the household corridor usage information derived from license plate observations. Generalized linear models have been used to link users’ travel behavior to socioeconomic attributes. Furthermore, GIS raster analysis methods have been utilized to visualize and quantify the impact of the HOV-to-HOT conversion on the corridor commutershed. At the local level, this study conducted a comprehensive socio-spatial analysis of the Atlanta I-85 HOV to HOT conversion. At the general scale, this study enhances managed lanes’ travel demand models with respect to users’ characteristics and introduces a comprehensive modeling framework for the socioeconomic analysis of managed lanes. The methods developed through this research will inform future Traffic and Revenue Studies and help to better predict the socio-spatial characteristics of the target market.

Les données comptées (count data) possèdent des distributions ayant des caractéristiques particulières comme la non-normalité, l’hétérogénéité des variances ainsi qu’un nombre important de zéros. Il est donc nécessaire d’utiliser les modèles appropriés afin d’obtenir des résultats non biaisés. Ce mémoire compare quatre modèles d’analyse pouvant être utilisés pour les données comptées : le modèle de Poisson, le modèle binomial négatif, le modèle de Poisson avec inflation du zéro et le modèle binomial négatif avec inflation du zéro. À des fins de comparaisons, la prédiction de la proportion du zéro, la confirmation ou l’infirmation des différentes hypothèses ainsi que la prédiction des moyennes furent utilisées afin de déterminer l’adéquation des différents modèles. Pour ce faire, le nombre d’arrestations des membres de gangs de rue sur le territoire de Montréal fut utilisé pour la période de 2005 à 2007. L’échantillon est composé de 470 hommes, âgés de 18 à 59 ans. Au terme des analyses, le modèle le plus adéquat est le modèle binomial négatif puisque celui-ci produit des résultats significatifs, s’adapte bien aux données observées et produit une proportion de zéro très similaire à celle observée. / Count data have distributions with specific characteristics such as non-normality, heterogeneity of variances and a large number of zeros. It is necessary to use appropriate models to obtain unbiased results. This memoir compares four models of analysis that can be used for count data: the Poisson model, the negative binomial model, the Poisson model with zero inflation and the negative binomial model with zero inflation. For purposes of comparison, the prediction of the proportion of zero, the confirmation or refutation of the various assumptions and the prediction of average number of arrrests were used to determine the adequacy of the different models. To do this, the number of arrests of members of street gangs in the Montreal area was used for the period 2005 to 2007. The sample consisted of 470 men, aged 18 to 59 years. After the analysis, the most suitable model is the negative binomial model since it produced significant results, adapts well to the observed data and produces a zero proportion very similar to that observed.

Recruitment of pelagic fish populations is believed to be regulated during the planktonic larval stage due to high rates of mortality during the early life stages. Starvation is thought to be one of the main sources of mortality, despite the fact that there is rarely a strong correlation between the feeding success of larval fish and food availability as measured in the field. This lack of relationship may be caused in part by (i) inadequate sampling of larval fish prey and (ii) the use of total zooplankton abundance or biomass as proxies for larval food availability. Many feeding studies rely on measures of average prey abundance which do not adequately capture the variability, or patchiness, of the prey field as experienced by larval fish. Previous studies have shown that larvae may rely on these patches to increase their feeding success. I assess the variability in the availability of larval fish prey over a range of scales and model the small-scale distribution of prey in Conception Bay, Newfoundland. I show that the greatest variability in zooplankton abundance existed at the meter scale, and that larval fish prey were not randomly distributed within the upper mixed layer. This will impact both how well we can model the stochastic nature of larval fish cohorts, as well as how well we can study larval fish feeding from gut content analyses. Expanding on six years of previous lab and field studies on larval Radiated Shanny (Ulvaria subbifurcata) from Conception Bay, Newfoundland, I assess the feeding success, niche breadth (S) and weight-specific feeding rates (SPC, d-1) of the larvae to determine whether there are size-based patterns evident across the years. I found that both the amount of food in the guts and the niche breadth of larvae increased with larval size. There was a shift from low to high SPC with increasing larval size, suggesting that foraging success increases as the larvae grow. My results suggest that efforts should be made to estimate the variability of prey abundance at scales relevant to larval fish foraging rather than using large-scale average abundance estimates, since small-scale prey patchiness likely plays a role in larval fish feeding dynamics. In addition, the characteristics of zooplankton (density, size and behaviour) should be assessed as not all zooplankton are preyed upon equally by all sizes of larval fish. Overall, this thesis demonstrates that indices based on averages fail to account for the variability in the environment and in individual larval fish, which may be confounding the relationship between food availability and larval growth.

Recruitment of pelagic fish populations is believed to be regulated during the planktonic larval stage due to high rates of mortality during the early life stages. Starvation is thought to be one of the main sources of mortality, despite the fact that there is rarely a strong correlation between the feeding success of larval fish and food availability as measured in the field. This lack of relationship may be caused in part by (i) inadequate sampling of larval fish prey and (ii) the use of total zooplankton abundance or biomass as proxies for larval food availability. Many feeding studies rely on measures of average prey abundance which do not adequately capture the variability, or patchiness, of the prey field as experienced by larval fish. Previous studies have shown that larvae may rely on these patches to increase their feeding success. I assess the variability in the availability of larval fish prey over a range of scales and model the small-scale distribution of prey in Conception Bay, Newfoundland. I show that the greatest variability in zooplankton abundance existed at the meter scale, and that larval fish prey were not randomly distributed within the upper mixed layer. This will impact both how well we can model the stochastic nature of larval fish cohorts, as well as how well we can study larval fish feeding from gut content analyses. Expanding on six years of previous lab and field studies on larval Radiated Shanny (Ulvaria subbifurcata) from Conception Bay, Newfoundland, I assess the feeding success, niche breadth (S) and weight-specific feeding rates (SPC, d-1) of the larvae to determine whether there are size-based patterns evident across the years. I found that both the amount of food in the guts and the niche breadth of larvae increased with larval size. There was a shift from low to high SPC with increasing larval size, suggesting that foraging success increases as the larvae grow. My results suggest that efforts should be made to estimate the variability of prey abundance at scales relevant to larval fish foraging rather than using large-scale average abundance estimates, since small-scale prey patchiness likely plays a role in larval fish feeding dynamics. In addition, the characteristics of zooplankton (density, size and behaviour) should be assessed as not all zooplankton are preyed upon equally by all sizes of larval fish. Overall, this thesis demonstrates that indices based on averages fail to account for the variability in the environment and in individual larval fish, which may be confounding the relationship between food availability and larval growth.

Cette thèse étudie le traitement statistique des images TEP. Plus particulièrement, la distribution binomiale négative est proposée pour modéliser l’activité d’une région mono-tissulaire. Cette représentation a l’avantage de pouvoir prendre en compte les variations d’activité biologique (ou hétérogénéité) d’un même tissu. A partir de ces résultats, il est proposé de modéliser la distribution de l’image TEP entière comme un mélange spatialement cohérent de lois binomiales négatives. Des méthodes Bayésiennes sont considérées pour la segmentation d’images TEP et l’estimation conjointe des paramètres du modèle. La cohérence spatiale inhérente aux tissus biologiques est modélisée par un champ aléatoire de Potts-Markov pour représenter la dépendance locale entre les composantes du mélange. Un algorithme original de Monte Carlo par Chaîne de Markov (MCMC) est utilisé, faisant appel aux notions d’échantillonnage dans un espace Riemannien et d’opérateurs proximaux. L’approche proposée est appliquée avec succès à la segmentation de tumeurs en imagerie TEP. Cette méthode est ensuite étendue d’une part en intégrant au processus de segmentation des informations anatomiques acquises par tomodensitométrie (TDM), et d’autre part en traitant une série temporelle d’images correspondant aux différentes phases de respiration. Un modèle de mélange de distributions bivariées binomiale négative - normale est proposé pour représenter les images dynamiques TEP et TDM fusionnées. Un modèle Bayésien hiérarchique a été élaboré comprenant un champ de Potts-Markov à quatre dimensions pour respecter la cohérence spatiale et temporelle des images PET-TDM dynamiques. Le modèle proposé montre une bonne qualité d’ajustement aux données et les résultats de segmentation obtenus sont visuellement en concordance avec les structures anatomiques et permettent la délimitation et le suivi de la tumeur. / This thesis studies statistical image processing of PET images. More specifically, the negative binomial distribution is proposed to model the activity of a single tissue. This representation has the advantage to take into account the variations of biological activity (or heterogeneity) within a single tissue. Based on this, it is proposed to model the data of the entire PET image as a spatially coherent finite mixture of negative binomial distributions. Bayesian methods are considered to jointly perform the segmentation and estimate the model parameters. The inherent spatial coherence of the biological tissue is modeled by a Potts-Markov random field to represent the local dependence between the components of the mixture. An original Markov Chain Monte Carlo (MCMC) algorithm is proposed, based on sampling in a Riemannian space and proximal operators. The proposed approach is successfully applied to the segmentation of tumors in PET imaging. This method is further extended by incorporating anatomical information acquired by computed tomography (CT) and processing a time series of images corresponding to the phases of respiration. A mixture model of bivariate negative binomial - normal distributions is proposed to represent the dynamic PET and CT fused images. A hierarchical Bayesian model was developed including a four dimensional Potts-Markov field to enforce the spatiotemporal coherence of dynamic PET-CT images. The proposed model shows a good fit to the data and the segmentation results obtained are visually consistent with the anatomical structures and allow accurate tumor delineation and tracking.