Analyse bayésienne et classification pour modèles continus modifiés à zéro

Les modèles à sur-représentation de zéros discrets et continus ont une large gamme d'applications et leurs propriétés sont bien connues. Bien qu'il existe des travaux portant sur les modèles discrets à sous-représentation de zéro et modifiés à zéro, la formulation usuelle des modèles continus à sur-représentation -- un mélange entre une densité continue et une masse de Dirac -- empêche de les généraliser afin de couvrir le cas de la sous-représentation de zéros. Une formulation alternative des modèles continus à sur-représentation de zéros, pouvant aisément être généralisée au cas de la sous-représentation, est présentée ici. L'estimation est d'abord abordée sous le paradigme classique, et plusieurs méthodes d'obtention des estimateurs du maximum de vraisemblance sont proposées. Le problème de l'estimation ponctuelle est également considéré du point de vue bayésien. Des tests d'hypothèses classiques et bayésiens visant à déterminer si des données sont à sur- ou sous-représentation de zéros sont présentées. Les méthodes d'estimation et de tests sont aussi évaluées au moyen d'études de simulation et appliquées à des données de précipitation agrégées. Les diverses méthodes s'accordent sur la sous-représentation de zéros des données, démontrant la pertinence du modèle proposé. Nous considérons ensuite la classification d'échantillons de données à sous-représentation de zéros. De telles données étant fortement non normales, il est possible de croire que les méthodes courantes de détermination du nombre de grappes s'avèrent peu performantes. Nous affirmons que la classification bayésienne, basée sur la distribution marginale des observations, tiendrait compte des particularités du modèle, ce qui se traduirait par une meilleure performance. Plusieurs méthodes de classification sont comparées au moyen d'une étude de simulation, et la méthode proposée est appliquée à des données de précipitation agrégées provenant de 28 stations de mesure en Colombie-Britannique.

Essays in partial identification and applications to treatment effects and policy evaluation.

Dans cette thèse, je me suis interessé à l’identification partielle des effets de traitements dans différents modèles de choix discrets avec traitements endogènes. Les modèles d’effets de traitement ont pour but de mesurer l’impact de certaines interventions sur certaines variables d’intérêt. Le type de traitement et la variable d’intérêt peuvent être défini de manière générale afin de pouvoir être appliqué à plusieurs différents contextes. Il y a plusieurs exemples de traitement en économie du travail, de la santé, de l’éducation, ou en organisation industrielle telle que les programmes de formation à l’emploi, les techniques médicales, l’investissement en recherche et développement, ou l’appartenance à un syndicat. La décision d’être traité ou pas n’est généralement pas aléatoire mais est basée sur des choix et des préférences individuelles. Dans un tel contexte, mesurer l’effet du traitement devient problématique car il faut tenir compte du biais de sélection. Plusieurs versions paramétriques de ces modèles ont été largement étudiées dans la littérature, cependant dans les modèles à variation discrète, la paramétrisation est une source importante d’identification. Dans un tel contexte, il est donc difficile de savoir si les résultats empiriques obtenus sont guidés par les données ou par la paramétrisation imposée au modèle. Etant donné, que les formes paramétriques proposées pour ces types de modèles n’ont généralement pas de fondement économique, je propose dans cette thèse de regarder la version nonparamétrique de ces modèles. Ceci permettra donc de proposer des politiques économiques plus robustes. La principale difficulté dans l’identification nonparamétrique de fonctions structurelles, est le fait que la structure suggérée ne permet pas d’identifier un unique processus générateur des données et ceci peut être du soit à la présence d’équilibres multiples ou soit à des contraintes sur les observables. Dans de telles situations, les méthodes d’identifications traditionnelles deviennent inapplicable d’où le récent développement de la littérature sur l’identification dans les modèles incomplets. Cette littérature porte une attention particuliere à l’identification de l’ensemble des fonctions structurelles d’intérêt qui sont compatibles avec la vraie distribution des données, cet ensemble est appelé : l’ensemble identifié. Par conséquent, dans le premier chapitre de la thèse, je caractérise l’ensemble identifié pour les effets de traitements dans le modèle triangulaire binaire. Dans le second chapitre, je considère le modèle de Roy discret. Je caractérise l’ensemble identifié pour les effets de traitements dans un modèle de choix de secteur lorsque la variable d’intérêt est discrète. Les hypothèses de sélection du secteur comprennent le choix de sélection simple, étendu et généralisé de Roy. Dans le dernier chapitre, je considère un modèle à variable dépendante binaire avec plusieurs dimensions d’hétérogéneité, tels que les jeux d’entrées ou de participation. je caractérise l’ensemble identifié pour les fonctions de profits des firmes dans un jeux avec deux firmes et à information complète. Dans tout les chapitres, l’ensemble identifié des fonctions d’intérêt sont écrites sous formes de bornes et assez simple pour être estimées à partir des méthodes d’inférence existantes.

Theoretical approach to the magnetostructural correlations in spin-Peierls compound CuGeO3

A theoretical density-functional study has been carried out to analyze the exchange coupling in the chains of CuGeO3 using discrete models. The results show a good agreement with the experimental exchange coupling constant (J) together with a strong dependence of J with the Cu-O-Cu angle. The calculation of the J values for a distorted model indicates a larger degree of dimerization than those reported previously.

The prediction of seasonal and inter-annual climate variations and their impacts on the water resources in the eastern seaboard of Thailand

The research of this thesis dissertation covers developments and applications of short-and long-term climate predictions. The short-term prediction emphasizes monthly and seasonal climate, i.e. forecasting from up to the next month over a season to up to a year or so. The long-term predictions pertain to the analysis of inter-annual- and decadal climate variations over the whole 21st century. These two climate prediction methods are validated and applied in the study area, namely, Khlong Yai (KY) water basin located in the eastern seaboard of Thailand which is a major industrial zone of the country and which has been suffering from severe drought and water shortage in recent years. Since water resources are essential for the further industrial development in this region, a thorough analysis of the potential climate change with its subsequent impact on the water supply in the area is at the heart of this thesis research. The short-term forecast of the next-season climate, such as temperatures and rainfall, offers a potential general guideline for water management and reservoir operation. To that avail, statistical models based on autoregressive techniques, i.e., AR-, ARIMA- and ARIMAex-, which includes additional external regressors, and multiple linear regression- (MLR) models, are developed and applied in the study region. Teleconnections between ocean states and the local climate are investigated and used as extra external predictors in the ARIMAex- and the MLR-model and shown to enhance the accuracy of the short-term predictions significantly. However, as the ocean state – local climate teleconnective relationships provide only a one- to four-month ahead lead time, the ocean state indices can support only a one-season-ahead forecast. Hence, GCM- climate predictors are also suggested as an additional predictor-set for a more reliable and somewhat longer short-term forecast. For the preparation of “pre-warning” information for up-coming possible future climate change with potential adverse hydrological impacts in the study region, the long-term climate prediction methodology is applied. The latter is based on the downscaling of climate predictions from several single- and multi-domain GCMs, using the two well-known downscaling methods SDSM and LARS-WG and a newly developed MLR-downscaling technique that allows the incorporation of a multitude of monthly or daily climate predictors from one- or several (multi-domain) parent GCMs. The numerous downscaling experiments indicate that the MLR- method is more accurate than SDSM and LARS-WG in predicting the recent past 20th-century (1971-2000) long-term monthly climate in the region. The MLR-model is, consequently, then employed to downscale 21st-century GCM- climate predictions under SRES-scenarios A1B, A2 and B1. However, since the hydrological watershed model requires daily-scale climate input data, a new stochastic daily climate generator is developed to rescale monthly observed or predicted climate series to daily series, while adhering to the statistical and geospatial distributional attributes of observed (past) daily climate series in the calibration phase. Employing this daily climate generator, 30 realizations of future daily climate series from downscaled monthly GCM-climate predictor sets are produced and used as input in the SWAT- distributed watershed model, to simulate future streamflow and other hydrological water budget components in the study region in a multi-realization manner. In addition to a general examination of the future changes of the hydrological regime in the KY-basin, potential future changes of the water budgets of three main reservoirs in the basin are analysed, as these are a major source of water supply in the study region. The results of the long-term 21st-century downscaled climate predictions provide evidence that, compared with the past 20th-reference period, the future climate in the study area will be more extreme, particularly, for SRES A1B. Thus, the temperatures will be higher and exhibit larger fluctuations. Although the future intensity of the rainfall is nearly constant, its spatial distribution across the region is partially changing. There is further evidence that the sequential rainfall occurrence will be decreased, so that short periods of high intensities will be followed by longer dry spells. This change in the sequential rainfall pattern will also lead to seasonal reductions of the streamflow and seasonal changes (decreases) of the water storage in the reservoirs. In any case, these predicted future climate changes with their hydrological impacts should encourage water planner and policy makers to develop adaptation strategies to properly handle the future water supply in this area, following the guidelines suggested in this study.

Factores asociados a complicaciones post quirúrgicas en pacientes adultos con obstrucción intestinal mecánica en Bogotá, Colombia, período 2008 - 2014

Introducción: La obstrucción intestinal es una patología de alta prevalencia e impacto en los servicios de cirugía general a nivel mundial. El manejo de esta entidad puede ser médico o quirúrgico. Cuando se requiere intervención quirúrgica, se busca evitar el desarrollo de isquemia intestinal y resecciones intestinales; durante el postoperatorio, pueden existir complicaciones. El objetivo de este estudio es identificar los factores asociados al desarrollo de complicaciones post operatorias en un grupo de pacientes con obstrucción intestinal mecánica llevados a manejo quirúrgico. Metodología: Estudio analítico tipo casos y controles en un grupo de pacientes con diagnóstico de obstrucción intestinal mecánica llevados a manejo quirúrgico de su patología. Los casos corresponden a los pacientes con complicaciones postoperatorias y los controles aquellos que no presentaron complicaciones. Se identificaron factores asociados a complicación post operatoria mediante modelos estadísticos bivariados y multivariados de regresión logística para factores como edad, sexo, antecedente quirúrgico, presentación clínica, paraclínica y diagnóstico postoperatorio de malignidad, entre otras. Resultados: Se identificaron un total de 138 pacientes (54 casos y 129 controles). Los rangos de edad entre 55-66 años y mayor de 66 años fueron asociados con complicaciones postoperatorias (OR 3,87 IC95% 1,58-9,50 y OR 3,62 IC95% 1,45-9,08 respectivamente). El déficit de base inferior a 5 mEq/litro se relaciona con complicaciones postoperatorias (OR 2,64 IC95% 1.33-5,25) Otras pruebas de laboratorio, características radiológicas, hallazgos de malignidad en el postoperatorio y la evolución de los pacientes no fueron asociados con complicaciones. Conclusiones: Las disminución de las complicaciones durante el manejo quirúrgico de obstrucción intestinal mecánica continúa siendo un reto para la cirugía general. Factores no modificables como edad avanzada y modificables como el equilibrio ácido base deben ser tenidos en cuenta dada su correlación en el desarrollo de complicaciones postoperatorias.

Mathematical modelling for the digital society

We argue the case for a new branch of mathematics and its applications: Mathematics for the Digital Society. There is a challenge for mathematics, a strong “pull” from new and emerging commercial and public activities; and a need to train and inspire a generation of quantitative scientists who will seek careers within the associated sectors. Although now going through an early phase of boiling up, prior to scholarly distillation, we discuss how data rich activities and applications may benefit from a wide range of continuous and discrete models, methods, analysis and inference. In ten years time such applications will be common place and associated courses may be embedded within the undergraduate curriculum.

Multivariate analysis of the dielectric response of materials modeled using networks of resistors and capacitors

We discuss the modeling of dielectric responses of electromagnetically excited networks which are composed of a mixture of capacitors and resistors. Such networks can be employed as lumped-parameter circuits to model the response of composite materials containing conductive and insulating grains. The dynamics of the excited network systems are studied using a state space model derived from a randomized incidence matrix. Time and frequency domain responses from synthetic data sets generated from state space models are analyzed for the purpose of estimating the fraction of capacitors in the network. Good results were obtained by using either the time-domain response to a pulse excitation or impedance data at selected frequencies. A chemometric framework based on a Successive Projections Algorithm (SPA) enables the construction of multiple linear regression (MLR) models which can efficiently determine the ratio of conductive to insulating components in composite material samples. The proposed method avoids restrictions commonly associated with Archie’s law, the application of percolation theory or Kohlrausch-Williams-Watts models and is applicable to experimental results generated by either time domain transient spectrometers or continuous-wave instruments. Furthermore, it is quite generic and applicable to tomography, acoustics as well as other spectroscopies such as nuclear magnetic resonance, electron paramagnetic resonance and, therefore, should be of general interest across the dielectrics community.

Clinical risk factors for osteoporotic fractures in Brazilian women and men: the Brazilian Osteoporosis Study (BRAZOS)

The Brazilian Osteoporosis Study (BRAZOS) is the first epidemiological study carried out in a representative sample of Brazilian men and women aged 40 years or older. The prevalence of fragility fractures is about 15.1% in the women and 12.8% in the men. Moreover, advanced age, sedentarism, family history of hip fracture, current smoking, recurrent falls, diabetes mellitus and poor quality of life are the main clinical risk factors associated with fragility fractures. The Brazilian Osteoporosis Study (BRAZOS) is the first epidemiological study carried out in a representative sample of Brazilian men and women aged 40 years or older with the purpose of identifying the prevalence and the main clinical risk factors (CRF) associated with osteoporotic fracture in our population. A total of 2,420 individuals (women, 70%) from 150 different cities in the five geographic regions in Brazil, and all different socio-economical classes were selected to participate in the present survey. Anthropometrical data as well as life habits, fracture history, food intake, physical activity, falls and quality of life were determined by individual quantitative interviews. The representative sampling was based on Brazilian National data provided by the 2000 and 2003 census. Low trauma fracture was defined as that resulting of a fall from standing height or less in individuals 50 years or older at specific skeletal sites: forearm, femur, ribs, vertebra and humerus. Sampling error was 2.2% with 95% confidence intervals. Logistic regression analysis models were designed having the fragility fracture as the dependent variable and all other parameters as the independent variable. Significance level was set as p < 0.05. The average of age, height and weight for men and women were 58.4 +/- 12.8 and 60.1 +/- 13.7 years, 1.67 +/- 0.08 and 1.56 +/- 0.07 m and 73.3 +/- 14.7 and 64.7 +/- 13.7 kg, respectively. About 15.1% of the women and 12.8% of the men reported fragility fractures. In the women, the main CRF associated with fractures were advanced age (OR = 1.6; 95% CI 1.06-2.4), family history of hip fracture (OR = 1.7; 95% CI 1.1-2.8), early menopause (OR = 1.7; 95% CI 1.02-2.9), sedentary lifestyle (OR = 1.6; 95% CI 1.02-2.7), poor quality of life (OR = 1.9; 95% CI 1.2-2.9), higher intake of phosphorus (OR = 1.9; 95% CI 1.2-2.9), diabetes mellitus (OR = 2.8; 95% CI 1.01-8.2), use of benzodiazepine drugs (OR = 2.0; 95% CI 1.1-3.6) and recurrent falls (OR = 2.4; 95% CI 1.2-5.0). In the men, the main CRF were poor quality of life (OR = 3.2; 95% CI 1.7-6.1), current smoking (OR = 3.5; 95% CI 1.28-9.77), diabetes mellitus (OR = 4.2; 95% CI 1.27-13.7) and sedentary lifestyle (OR = 6.3; 95% CI 1.1-36.1). Our findings suggest that CRF may contribute as an important tool to identify men and women with higher risk of osteoporotic fractures and that interventions aiming at specific risk factors (quit smoking, regular physical activity, prevention of falls) may help to manage patients to reduce their risk of fracture.

Análise de desempenho de vendas em telecomunicações utilizando técnicas de mineração de dados

Nowadays, telecommunications is one of the most dynamic and strategic areas in the world. Organizations are always seeking to find new management practices within an ever increasing competitive environment where resources are getting scarce. In this scenario, data obtained from business and corporate processes have even greater importance, although this data is not yet adequately explored. Knowledge Discovery in Databases (KDD) appears then, as an option to allow the study of complex problems in different areas of management. This work proposes both a systematization of KDD activities using concepts from different methodologies, such as CRISP-DM, SEMMA and FAYYAD approaches and a study concerning the viability of multivariate regression analysis models to explain corporative telecommunications sales using performance indicators. Thus, statistical methods were outlined to analyze the effects of such indicators on the behavior of business productivity. According to business and standard statistical analysis, equations were defined and fit to their respective determination coefficients. Tests of hypotheses were also conducted on parameters with the purpose of validating the regression models. The results show that there is a relationship between these development indicators and the amount of sales

Valores de referência para o teste de caminhada com carga progressiva em indivíduos saudáveis: da distância percorrida às respostas fisiológicas

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Modeling grouped survival data with time-dependent covariates

In this article, proportional hazards and logistic models for grouped survival data were extended to incorporate time-dependent covariates. The extension was motivated by a forestry experiment designed to compare five different water stresses in Eucalyptus grandis seedlings. The response was the seedling lifetime. The data set was grouped since there were just three occasions in which the seedlings was visited by the researcher. In each of these occasions also the shoot height was measured and therefore it is a time-dependent covariate. Both extended models were used in this example, and the results were very similar.

Serum Metalloproteinases 2 and 9 as Predictors of Gait Status, Pressure Ulcer and Mortality after Hip Fracture

Introduction: The aim of this study is to evaluate the serum activity of metalloproteinases (MMPs) -2 and -9 as predictors of pressure ulcer (PU), gait status and mortality 6 months after hip fracture. Methods: Eighty-seven patients over the age of 65 admitted to the orthopedic unit from January to December 2010 with hip fracture were prospectively evaluated. Upon admission, patient demographic information, including age, gender and concomitant diseases, was recorded. Blood samples were taken for analysis of MMP -2 and -9 activity by gel zymography and for biochemical examination within the first 72 hours of the patient's admission, after clinical stabilization. The fracture pattern (neck, trochanteric or subtrochanteric), time from admission to surgery, surgery duration and length of hospital stay were also recorded. Results: Two patients were excluded due to the presence of pathological fractures (related to cancer), and three patients were excluded due to the presence of PU before admission. Eighty-two patients, with a mean age of 80.4 ± 7.3 years, were included in the analysis. Among these patients, 75.6% were female, 59.8% had PU, and 13.4% died 6 months after hip fracture. All patients underwent hip fracture repair. In a univariate analysis, there were no differences in serum MMP activity between hip fracture patients with or without PU. In addition, the multiple logistic regression analysis models, which were adjusted by age, gender, length of hospital stay and C-reactive protein, showed that the pro-MMP-9 complexed with neutrophil gelatinase-associated lipocalin form (130 kDa) was associated with gait status recovery 6 months after hip fracture. Conclusions: In conclusion, serum pro-MMP-9 is a predictor of gait status recovery 6 months after hip fracture. © 2013 Gumieiro et al.

Regressão logística aplicada na análise espacial de dados arqueológicos

Pós-graduação em Ciências Cartográficas - FCT

Os modelos de crescimento populacional de Malthus e Verhulst: uma motivação para o ensino de logaritmos e exponenciais

Pós-graduação em Matemática em Rede Nacional - IBILCE

Análise do comportamento experimental e numérico de prismas de alvenaria estrutural submetidos a ações verticais utilizando elementos finitos volumétricos

Pós-graduação em Engenharia Civil - FEIS