Made available in DSpace on 2014-06-11T19:26:15Z (GMT). No. of bitstreams: 0 Previous issue date: 2011-02-18Bitstream added on 2014-06-13T20:34:05Z : No. of bitstreams: 1 euzebio_rd_me_sjrp.pdf: 535663 bytes, checksum: 91f53fae0870b5e3f322f71d88e2b2e4 (MD5) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Nosso objetivo neste trabalho é estudar o método do averaging através do grau topológico de Brouwer e utilizá-lo para investigar o número de ciclos limites que bifurcam de uma singularidade do tipo centro quando perturbamos um sistema de equações diferenciais através de um pequeno parâmetro ε. Começaremos apresentando o método do averaging que aaprece na literatura clássica e algumas aplicações deste. Depois faremos uma breve discussão sobre o grau topológico de Brouwer, seguido do teorema do averaging que faz menção a este conceito. Finalmente, exibiremos algumas aplicações inéditas do método. / The aim of this is to study the averaging method using the Brouwer topological degree in order to investigative the number of limit cycles that can bifurcate from a center type singularity when a differential systemas is perturbed by a small parameter ε. To this respect, initially, we present classical averaging method and some of its applications. So we introduce the Brouwer topological degree, followed by the averaging theorem. Finally, we show some original applications of the averaging method.

Made available in DSpace on 2016-06-02T20:06:12Z (GMT). No. of bitstreams: 1 DissJBB.pdf: 632747 bytes, checksum: 7f6e8caa78736a965ecb167ee27b7cc3 (MD5) Previous issue date: 2006-04-18 / Universidade Federal de Sao Carlos / This work consider the problem of how to incorporate model selection uncertainty into statistical inference, through model averaging, applied to logistic regression. It will be used the approach of Buckland et. al. (1997), that proposed an weighed estimator to a parameter common to all models in study, where the weights are obtained by information criteria or bootstrap method. Also will be applied bayesian model averaging as shown by Hoeting et. al. (1999), where posterior probability is an average of the posterior distributions under each of the models considered, weighted by their posterior model probability. The aim of this work is to study the behavior of the weighed estimator, both, in the classic approach and in the bayesian, in situations that consider the use of binary logistic regression, with foccus in prediction. The known model-choice selection method Stepwise will be considered as form of comparison of the predictive performance in relation to model averaging. / Esta dissertação considera o problema de incorporação da incerteza devido à escolha do modelo na inferência estatística, segundo a abordagem de ponderação de modelos, com aplicação em regressão logística. Será utilizada a abordagem de Buckland et. al. (1997), que propuseram um estimador ponderado para um parâmetro comum a todos os modelos em estudo, sendo que, os pesos desta ponderação são obtidos a partir do uso de critérios de informação ou do método bootstrap. Também será aplicada a ponderação bayesiana de modelos como apresentada por Hoeting et. al. (1999), onde a distribuição a posteriori do parâmetro de interesse é uma média da distribuição a posteriori do parâmetro sob cada modelo em consideração ponderado por suas respectivas probabilidades a posteriori. O objetivo deste trabalho é estudar o comportamento do estimador ponderado, tanto na abordagem clássica como na bayesiana, em situações que consideram o uso de regressão logística binária, com enfoque na estimação da predição. O método de seleção de modelos Stepwise será considerado como forma de comparação da capacidade preditiva em relação ao método de ponderação de modelos.

In the recent years, prices of art have repeatedly broken records, and the interest in investing in fine art photography has been growing. Although there is plenty of research dedicated to studying prices of paintings, fine art photography has been largely overlooked. This thesis aims to shed light on identifying price determinants for this particular medium. A new data set is collected from sold lot archives of Sotheby's and Phillips auction houses, which also provide images of some of the sold items. These images are then used to create new variables describing visual attributes of the artworks. In order to inspect the effect of color-related predictors on price, four different methods are discussed. Color is found to be significant in OLS model, but the effect diminishes when model averaging is applied. Machine learning al- gorithms - regression trees and random forests - suggest that the importance of color is relatively low. The thesis also shows that expert estimates can improved by incorporating available information and using random forests for prediction. The fact that the expert estimates are not very accurate sug- gest that they either do not use all the available information or they do not process it efficiently. 1

This thesis studies the relationship between GDP and Social Progress Index, components of social progress model and their dimensions. Using the dataset of 49 countries and Bayesian Model Averaging (BMA) and clustering analysis we found that there is not straight relationship between GDP and SPI. By testing 15 different models for each of 3 dimension (Basic Human Needs, Foundations of Wellbeing and Opportunity) of SPI we have found that the best variation of components would be to include all of them for each dimension. By using BMA approach we have found that the best model of SPI out of 12 components includes only intercept, tolerance and inclusion variables. The rest of components show quite low probability of inclusion, however, none of them showed 0 posterior probability. JEL Classification A13, C11, E01, I30, Keywords Kuznets, progress, SPI, GDP, BMA Author's e-mail valeria.e.efimenko@gmail.com Supervisor's e-mail daniel.vach@gmail.com

Orientador: Claudio Aguinaldo Buzzi / Banca: Maurício Firmino Silva Lima / Banca: Marcelo Messias / Resumo: Neste trabalho estudamos o Método Averaging. Este método é uma ferramenta extremamente útil para quantificar o número de ciclos limites que podem bifurcar de uma singularidade do tipo centro de um sistema de equações diferenciais. A parte inicial do trabalho apresenta a Teoria de Aproximação Assintótica e um primeiro contato com o Averaging. Posteriormente apresentamos uma versão do Averaging via a Teoria do Grau de Brouwer. Finalmente fizemos algumas aplicações do método apresentando uma cota superior para o número de ciclos limites que podem bifurcar a partir das órbitas periódicas de centros de um sistema de equações diferenciais. Além disso, mostramos através de exemplos concretos que esta cota superior pode ser realizada. / Abstract: In this work we study the Averaging Method. This method is a useful tool in order to give the maximum number of limit cycles that can bifurcate from a center type singularity of a di®erential equation system. In the first part of the work we present the Asymptotic Approximation Theory and a first view of the averaging. After that, we present a version of the averaging via Brouwer Degree Theory. Finally we give some applications of this method presenting an upper bound for the number of limit cycles that can bifurcate from a center type singularity of a di®erential equation system. Moreover, we show by presenting concrete examples that this upper bound can be realized. / Mestre

Orientador: Paulo Régis Caron Ruffino / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Matemática Estatística e Computação Científica / Made available in DSpace on 2018-08-23T11:21:58Z (GMT). No. of bitstreams: 1 Costa_PauloHenriquePereirada_D.pdf: 1382380 bytes, checksum: 975aac3916932e92b8fe92b185b6eb9f (MD5) Previous issue date: 2013 / Resumo: Seja (M,?) uma variedade Riemanniana compacta folheada. Consideramos uma família de semigrupos Feller compatível em C(Mn) associada as leis de um processo Markoviano de n-pontos. Com algumas condições (Le Jan e Raimond [34]) existe um fluxo estocástico de aplicações mensuráveis em M. Estudamos aqui a degenerescência desses semigrupos tais que o fluxo de aplicações seja folheado, ou seja, cada trajetória permanece na folha em que começou q.s. e portanto cria uma obstrução geométrica natural para a coalescência de trajetórias em folhas distintas. Como uma aplicação dessa teoria, um princípio de médias é provado para uma perturbação de primeira ordem transversal as folhas. Estimativas de taxas de convergências também são dadas / Abstract: Let (M,?) be a compact Riemannian foliated manifold. We consider a family of compatible Feller semigroups in C(Mn) associated to laws of the n-point motion. Under some assumptions (Le Jan and Raimond [34]) there exists a stochastic flow of measurable mappings in M. We study the degeneracy of these semigroups such that the flow of mappings is foliated, i.e. each trajectory lays in a single leaf of the foliation a.s, hence creating a geometrical obstruction for coalescence of trajectories in different leaves. As an application, an averaging principle is proved for a first order perturbation transversal to the leaves. Estimates for the rate of convergence are calculated / Doutorado / Matematica / Doutor em Matemática

We propose the use of Latent Class Analysis methods to analyze the covariate inclusion patterns across specifications resulting from Bayesian model averaging exercises. Using Dirichlet Process clustering, we are able to identify and describe dependency structures among variables in terms of inclusion in the specifications that compose the model space. We apply the method to two datasets of potential determinants of economic growth. Clustering the posterior covariate inclusion structure of the model space formed by linear regression models reveals interesting patterns of complementarity and substitutability across economic growth determinants.

Approved for public release; distribution is unlimited / This thesis describes the procedure used for the automatic measurement of particles from hologram taken in the combustion chamber of a rocket motor while firing. It describes the investigation done on two averaging techniques used to reduce speckle noise, capturing the image focused on a spinning mylar disk and software averaging of several image frames. The spinning disk technique proved superior for this application. The Kolmogorov-Smirnov two-sample test is applied to different particle samples in order to find an estimate of the number of particles required to obtain a stable distribution function. The number of particles is calculated and given. The last part of this study shows real particle distributions in the form of frequency histograms. / http://archive.org/details/automaticmeasure00carr / Major, Canadian Armed Forces

The aim of this study is to apply computed order tracking with subsequent rotation domain averaging and statistical analysis to typical mining environments. Computed order tracking is a fault detection method that is unaffected by varying speed conditions often found in industry and has been proven effective in laboratory conditions. However in the controlled environment of a laboratory it is difficult to test the robustness of the order-tracking procedure. The need thus exists to adjust the order tracking procedure so that it will be effective in the mining environment. The procedure needs to be adjusted to function with a two pulse per revolution speed input. The drag gear aboard a dragline rotates in two directions. This gives the unique opportunity to observe the performance of the order tracking method in a bi-directional rotating environment allowing relationships between the results of each operating direction to be investigated. A monitoring station was set up aboard a dragline and data was captured twice daily for a period spanning one year. The data captured consisted of accelerometer and proximity sensor data. The key on the shaft triggers the proximity sensors allowing speed and direction to be measured. The rudimentary measured speed is interpolated using various documented speed interpolation techniques and by a newly developed speed interpolation technique. The interpolated speed is then used to complete the order tracking procedure that re-samples the vibration data with reference to the speed. The results indicate that computed order tracking can be successfully implemented in typical mining environments. Furthermore there is a distinct relationship between vibration data taken in both rotational directions: one direction provides a better indication of incipient failure. It is thus important not to choose a direction randomly when monitoring rotating machinery of this kind. / Dissertation (MEng)--University of Pretoria, 2008. / Mechanical and Aeronautical Engineering / unrestricted

The Sahel region located in Western Africa is well known for its high rainfall variability. Severe and recurring droughts have plagued the region during the last three decades of the 20th century, while heavy precipitation events (with return periods of up to 1,200 years) were reported between 2007 and 2014. Vulnerability to extreme events is partly due to the fact that people are not prepared to cope with them. It would be of great benefit to farmers if information about the magnitudes of precipitation and streamflow in the upcoming rainy season were available a few months before; they could then switch to more adapted crops and farm management systems if required. Such information would also be useful for other sectors of the economy, such as hydropower production, domestic/industrial water consumption, fishing and navigation. A logical solution to the above problem would be seasonal rainfall and streamflow forecasting, which would allow to generate knowledge about the upcoming rainy season based on information available before it's beginning. The research in this thesis sought to improve seasonal rainfall and streamflow forecasting in the Sahel by developing statistical rainfall and streamflow seasonal forecasting models. Sea surface temperature (SST) were used as pools of predictor. The developed method allowed for a systematic search of the best period to calculate the predictor before it was used to predict average rainfall or streamflow over the upcoming rainy season. Eight statistical models consisted of various statistical methods including linear and polynomial regressions were developed in this study. Two main approaches for seasonal streamflow forecasting were developed here: 1) A two steps streamflow forecasting approach (called the indirect method) which first linked the average SST over a period prior to the date of forecast to average rainfall amount in the upcoming rainy season using the eight statistical models, then linked the rainfall amount to streamflow using a rainfall-runoff model (Soil and Water Assessment Tool (SWAT)). In this approach, the forecasted rainfall was disaggregated to daily time step using a simple approach (the fragment method) before being fed into SWAT. 2) A one step streamflow forecasting approach (called as the direct method) which linked the average SST over a period prior to the date of forecast to the average streamflow in the upcoming rainy season using the eight statistical models. To decrease the uncertainty due to model selection, Bayesian Model Averaging (BMA) was also applied. This method is able to explore the possibility of combining all available potential predictors (instead of selecting one based on an arbitrary criterion). The BMA is also capability to produce the probability density of the forecast which allows end-users to visualize the density of expected value and assess the level of uncertainty of the generated forecast. Finally, the economic value of forecast system was estimated using a simple economic approach (the cost/loss ratio method). Each developed method was evaluated using three well known model efficiency criteria: the Nash-Sutcliffe coefficient (Ef), the coefficient of determination (R2) and the Hit score (H). The proposed models showed equivalent or better rainfall forecasting skills than most research conducted in the Sahel region. The linear model driven by the Pacific SST produced the best rainfall forecasts (Ef = 0.82, R2 = 0.83, and H = 82%) at a lead time of up to 12 months. The rainfall forecasting model based on polynomial regression and forced by the Atlantic ocean SST can be used using a lead time of up to 5 months and had a slightly lower performance (Ef = 0.80, R2 = 0.81, and H = 82%). Despite the fact that the natural relationship between rainfall and SST is nonlinear, this study found that good results can be achieved using linear models. For streamflow forecasting, the direct method using polynomial regression performed slightly better than the indirect method (Ef = 0.74, R2 = 0.76, and H = 84% for the direct method; Ef = 0.70, R2 = 0.69, and H = 77% for the indirect method). The direct method was driven by the Pacific SST and had five months lead time. The indirect method was driven by the Atlantic SST and had six months lead time. No significant difference was found in terms of performance between BMA and the linear regression models based on a single predictor for streamflow forecasting. However, BMA was able to provide a probabilistic forecast that accounts for model selection uncertainty, while the linear regression model had a longer lead time. The economic value of forecasts developed using the direct and indirect methods were estimated using the cost/loss ratio method. It was found that the direct method had a better value than the indirect method. The value of the forecast declined with higher return periods for all methods. Results also showed that for the particular watershed under investigation, the direct method provided a better information for flood protection. This research has demonstrated the possibility of decent seasonal streamflow forecasting in the Sirba watershed, using the tropical Pacific and Atlantic SSTs as predictors.The findings of this study can be used to improve the performance of seasonal streamflow forecasting in the Sahel. A package implementing the statistical models developed in this study was developed so that end users can apply them for seasonal rainfall or streamflow forecasting in any region they are interested in, and using any predictor they may want to try.