816 resultados para MIXED DISCRETE


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People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

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Tests for dependence of continuous, discrete and mixed continuous-discrete variables are ubiquitous in science. The goal of this paper is to derive Bayesian alternatives to frequentist null hypothesis significance tests for dependence. In particular, we will present three Bayesian tests for dependence of binary, continuous and mixed variables. These tests are nonparametric and based on the Dirichlet Process, which allows us to use the same prior model for all of them. Therefore, the tests are “consistent” among each other, in the sense that the probabilities that variables are dependent computed with these tests are commensurable across the different types of variables being tested. By means of simulations with artificial data, we show the effectiveness of the new tests.

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Thesis (Ph.D.)--University of Washington, 2016-08

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People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

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Often in biomedical research, we deal with continuous (clustered) proportion responses ranging between zero and one quantifying the disease status of the cluster units. Interestingly, the study population might also consist of relatively disease-free as well as highly diseased subjects, contributing to proportion values in the interval [0, 1]. Regression on a variety of parametric densities with support lying in (0, 1), such as beta regression, can assess important covariate effects. However, they are deemed inappropriate due to the presence of zeros and/or ones. To evade this, we introduce a class of general proportion density, and further augment the probabilities of zero and one to this general proportion density, controlling for the clustering. Our approach is Bayesian and presents a computationally convenient framework amenable to available freeware. Bayesian case-deletion influence diagnostics based on q-divergence measures are automatic from the Markov chain Monte Carlo output. The methodology is illustrated using both simulation studies and application to a real dataset from a clinical periodontology study.

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The aim of this work was to evaluate the floristic composition, richness, and diversity of the upper and lower strata of a stretch of mixed rain forest near the city of Itaberá, in southeastern Brazil. We also investigated the differences between this conservation area and other stretches of mixed rain forest in southern and southeastern Brazil, as well as other nearby forest formations, in terms of their floristic relationships. For our survey of the upper stratum (diameter at breast height [DBH] > 15 cm), we established 50 permanent plots of 10 × 20 m. Within each of those plots, we designated five, randomly located, 1 × 1 m subplots, in order to survey the lower stratum (total height > 30 cm and DBH < 15 cm). In the upper stratum, we sampled 1429 trees and shrubs, belonging to 134 species, 93 genera, and 47 families. In the lower stratum, we sampled 758 trees and shrubs, belonging to 93 species, 66 genera, and 39 families. In our floristic and phytosociological surveys, we recorded 177 species, belonging to 106 genera and 52 families. The Shannon Diversity Index was 4.12 and 3.5 for the upper and lower strata, respectively. Cluster analysis indicated that nearby forest formations had the strongest floristic influence on the study area, which was therefore distinct from other mixed rain forests in southern Brazil and in the Serra da Mantiqueira mountain range.

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This study was evaluated the response of subcutaneous connective tissue of isogenic mice to calcium hydroxide-based pastes with chlorhexidine digluconate (CHX). Seventy isogenic male BALB/c mice aged 6-8 weeks and weighing 15-20 g were randomly assigned to 8 groups. The animals received polyethylene tube implants as follows: Groups I, II, and III (n=10) - Calen® paste mixed with 0.4% CHX (experimental paste; Calen/CHX) for 7, 21, and 63 days, respectively; Groups IV, V, and VI (n=10) - UltraCal™ paste mixed with 2% CHX (experimental paste supplied by Ultradent Products Inc.; Ultracal/CHX) for 7, 21, and 63 days, respectively; and Groups VII and VIII (n=5): empty tube for 7 and 21 days, respectively. At the end of the experimental periods, the implants were removed together with the surrounding tissues (skin and subcutaneous connective tissue). The biopsied tissues were subjected to routine processing for histological analysis. Using a descriptive analysis and a four-point (0-3) scoring system, the following criteria were considered for qualitative and quantitative analysis of the tissue around the implanted materials: collagen fiber formation, tissue thickness and inflammatory infiltrate. A quantitative analysis was performed by measuring the thickness (µm), area (µm²) and perimeter (µm) of the reactionary granulomatous tissue formed at the tube ends. Data were analyzed statistically by the Kruskal-Wallis test and Dunn's post-test (α=0.05). Calen/CHX showed biocompatibility with the subcutaneous and reactionary tissues, with areas of discrete fibrosis and normal conjunctive fibrous tissue, though without statistically significant difference (p>0.05) from the control groups. In Groups I to III, there was a predominance of score 1, while in Groups IV to VI scores 2 and 3 predominated for all analyzed parameters. UltraCal/CHX, on the other hand, induced the formation of an inflammatory infiltrate and abundant exudate, suggesting a persistent residual aggression from the material, even 63 days after implant placement. In conclusion, the Calen paste mixed with 0.4% CHX allowed an adequate tissue response, whereas the UltraCal paste mixed with 2% CHX showed unsatisfactory results.

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Testing contexts have been shown to critically influence experimental results in psychophysical studies. One of these contexts that show important modulation of the behavioral effects of different stimulatory conditions is the separate (blocked) or mixed presentation of these stimulatory conditions. The study presents evidence that the apparent discriminabilities of two target stimuli can change according to which of these two testing contexts is used. A cross inside a ring and a vertical line inside a ring were presented as go stimuli in a go/no-go reaction time task. In one experiment, each of these stimuli was presented to a different group of volunteers and in another experiment they were presented to the same group of volunteers, randomly mixed in the blocks of trials. Similar reaction times were obtained for the two stimuli in the first experiment, and different reaction times (faster for the cross) in the second experiment. The latter result indicates that the two stimuli have different discriminabilities from the no-go stimulus; the cross having greater discriminability. This difference is however masked, presumably by the adoption of specific compensatory attentional sets, in a separate testing context.

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A study was performed in order to determine the efficiency of the simultaneous use of the photoinitiators phenylpropanedione (PPD) and camphorquinone (CQ) in the polymerization of acrylic polymers and evaluate possible mechanisms leading to synergism or antagonism. It was found that efficiencies of both initiators taken individually are higher than that of their mixture, indicating that when both dyes are used simultaneously there will be an energy transfer from the more efficient initiator (CQ) to the less efficient one (PPD). Also, there was no proof of any reaction between the amine present in the CQ formulation and the PPD excited state.

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This paper proposes a new design methodology for discrete multi-pumped Raman amplifier. In a multi-objective optimization scenario, in a first step the whole solution-space is inspected by a CW analytical formulation. Then, the most promising solutions are fully investigated by a rigorous numerical treatment and the Raman amplification performance is thus determined by the combination of analytical and numerical approaches. As an application of our methodology we designed an photonic crystal fiber Raman amplifier configuration which provides low ripple, high gain, clear eye opening and a low power penalty. The amplifier configuration also enables to fully compensate the dispersion introduced by a 70-km singlemode fiber in a 10 Gbit/s system. We have successfully obtained a configuration with 8.5 dB average gain over the C-band and 0.71 dB ripple with almost zero eye-penalty using only two pump lasers with relatively low pump power. (C) 2009 Optical Society of America

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Over the last couple of decades, many methods for synchronizing chaotic systems have been proposed with communications applications in view. Yet their performance has proved disappointing in face of the nonideal character of usual channels linking transmitter and receiver, that is, due to both noise and signal propagation distortion. Here we consider a discrete-time master-slave system that synchronizes despite channel bandwidth limitations and an allied communication system. Synchronization is achieved introducing a digital filter that limits the spectral content of the feedback loop responsible for producing the transmitted signal. Copyright (C) 2009 Marcio Eisencraft et al.

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We describe a case of a spontaneously established mixed colony of two species of stingless bees. The host colony of Scaptotrigona depilis, an aggressive bee that forms large colonies, was invaded by workers of Nannotrigona testaceicornis, a smaller bee that forms small colonies. The host colony and the invading species colony were maintained in next boxes about 1.5 m apart. The N. testaceicornis colony had been recently divided. Observations were made daily for 10 min, and every two weeks the colony was opened for observations within the nest. Initially the host colony bees repulsed the invading species, but as their numbers built up, they were no longer able to defend the entrance. An estimated 60-90 N. testaceicornis workers lived integrated into the colony of S. depilis for 58 days. During this period, they reconstructed and maintained the entrance tube, changing it to an entrance typical of N. testaceicornis. They also collected food and building material for the host colony. Nannotrigona testaceicornis tolerated transit of S. depilis through the entrance, but did not allow the host species to remain within the tube, though the attacks never resulted in bee mortality. Aggression was limited to biting the wings; when the bees fell to the ground they immediately separated and flew back. There have been very few reports of spontaneously occurring mixed stingless bee colonies. It is difficult to determine what caused the association that we found; probably workers of N. testaceicornis got lost when we split their colony, and then they invaded the colony of S. depilis.

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Chagas disease caused by Trypanosoma cruzi is a complex disease that is endemic and an important problem in public health in Latin America. The T. cruzi parasite is classified into six discrete taxonomic units (DTUs) based on the recently proposed nomenclature (TcI, TcII, TcIII, TcIV, TcV and TcVI). The discovery of genetic variability within TcI showed the presence of five genotypes (Ia, Ib, Ic, Id and Ie) related to the transmission cycle of Chagas disease. In Colombia, TcI is more prevalent but TcII has also been reported, as has mixed infection by both TcI and TcII in the same Chagasic patient. The objectives of this study were to determine the T. cruzi DTUs that are circulating in Colombian chronic Chagasic patients and to obtain more information about the molecular epidemiology of Chagas disease in Colombia. We also assessed the presence of electrocardiographic, radiologic and echocardiographic abnormalities with the purpose of correlating T. cruzi genetic variability and cardiac disease. Molecular characterization was performed in Colombian adult chronic Chagasic patients based on the intergenic region of the mini-exon gene, the 24S alpha and 18S regions of rDNA and the variable region of satellite DNA, whereby the presence of T. cruzi I, II, III and IV was detected. In our population, mixed infections also occurred, with TcI-TcII, TcI-TcIII and TcI-TcIV, as well as the existence of the TcI genotypes showing the presence of genotypes Ia and Id. Patients infected with TcI demonstrated a higher prevalence of cardiac alterations than those infected with TcII. These results corroborate the predominance of TcI in Colombia and show the first report of TcIII and TcIV in Colombian Chagasic patients. Findings also indicate that Chagas cardiomyopathy manifestations are more correlated with TcI than with TcII in Colombia.

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The radiation of angiosperms is associated with shifts among pollination modes that are thought to have driven the diversification of floral forms. However, the exact sequence of evolutionary events that led to such great diversity in floral traits is unknown for most plant groups. Here, we characterize the patterns of evolution of individual floral traits and overall floral morphologies in the tribe Bignonieae (Bignoniaceae). We identified 12 discrete traits that are associated with seven floral types previously described for the group and used a penalized likelihood tree of the tribe to reconstruct the ancestral states of those traits at all nodes of the phylogeny of Bignonieae. In addition, evolutionary correlations among traits were conducted using a maximum likelihood approach to test whether the evolution of individual floral traits followed the correlated patterns of evolution expected under the ""pollination syndrome"" concept. The ancestral Bignonieae flower presented an Anemopaegma-type morphology, which was followed by several parallel shifts in floral morphologies. Those shifts occurred through intermediate stages resulting in mixed floral morphologies as well as directly from the Anemopaegma-type morphology to other floral types. Positive and negative evolutionary correlations among traits fit patterns expected under the pollination syndrome perspective, suggesting that interactions between Bignonieae flowers and pollinators likely played important roles in the diversification of the group as a whole.

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We use QCD sum rules (QCDSR) to calculate the width of the radiative decay of the meson X(3872), assumed to be a mixture between charmonium and exotic molecular [c (q) over bar][q (c) over bar] states with J(PC) = 1(++). We find that in a small range for the values of the mixing angle, 5 degrees <= theta <= 13 degrees, we get the branching ratio Gamma(X -> J/psi gamma)/Gamma(X -> J/psi pi(+)pi(-)) = 0.19 +/- 0.13, which is in agreement, with the experimental value. This result is compatible with the analysis of the mass and decay width of the mode J/psi(n pi) performed in the same approach.