Line-Field Based Adaptive Image Model for Blind Deblurring

Ph.DDOCTOR OF PHILOSOPH

Bayesian population inference for effective connectivity

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.Includes bibliographical references (p. 157-169).A hierarchical model based on the Multivariate Autoregessive (MAR) process is proposed to jointly model functional neuroimaging time series collected from multiple subjects, and to characterize the distribution of MAR coefficients across the population from which those subjects were drawn. Thus, model-based inference about the interaction between brain regions, termed effective connectivity, may be generalized beyond those subjects studied. The posterior density of population- and subject-level connectivity parameters is estimated in a Variational Bayesian (VB) framework, and structural model parameters are chosen by the corresponding evidence criterion. The significance of resulting connectivity statistics are evaluated by permutation-based approximations to the null distribution. The method is demonstrated on simulated data and on actual multi-subject functional time series from electroencephalography (EEG) and functional magnetic resonance imaging (fMRI).by Eric Richard Cosman, Jr.Ph.D

Bayesian forecasting with state space models

This thesis explores the use of State-Space models in Time Series Analysis and Forecasting, with particular reference to the Dynamic Linear Model (DLM) introduced by Harrison and Stevens. Concepts from Control Theory are employed, especially those of observability, controllability and filtering, together with Bayesian inference and classical forecasting methodology. First, properties of state-space models which depart from the usual Gaussian assumptions are examined, and the predictive consequences of such models are developed. These models can lead to new phenomena, for example it is shown that for a wide class of models which have a suitably defined steady evolution the usual properties of classical steady models (such as exponentially weighted moving averages) do not apply. Secondly, by considering the forecast functions, equivalence theorems are proved for DLMs in the steady state and stationary Box-Jenkins models. These theorems are then extended to include both time-varying and non-stationary models thus establishing a very general predictor equivalence. However it is shown that intuitively appealing DLMs which have diagonal covariance matrices are restricted by only covering part of the equivalent stability / invertibility region, and examples are given to illustrate these points. Thirdly, some problems of inference involving state-space models are looked at, and new approaches outlined. A class of collapsing procedures based upon a distance measure between posterior components is introduced. This allows the use of non-normal errors or Harrison-Stevens Class II models by condensing the normal-mixture posterior distribution to prevent an explosion of information with time, and avoids some of the problems of the Harrison-Stevens solution. Finally, some examples are given to illustrate the way in which some of these models and collapsing procedures might be used in practice.<p

Essays on the determinants and spillovers of South African housing market

This study investigates the relevant factors that drive house prices in South Africa with the aim of facilitating a better understanding of the dynamic relationship between house prices and key macroeconomic variables. This can serve as a prerequisite to the ability of policymakers to maximize the positive externalities associated with housing development, while implementing measures to reduce the unexpected effects. The thesis consists of five independent papers corresponding to five chapters. The first chapter examines the economic sources underlying the comovement of real house prices across provinces in South Africa. First, a dynamic factor model is estimated on quarterly provincial-level data to disentangle the national component of real house price movements from the local (provincial or region-specific) component. Second, a Structural Vector Autoregressive (SVAR) model is applied to investigate the extent to which macroeconomic shocks are responsible to the common component of real house prices. Using theoretically motivated short run restrictions to identify macroeconomic with portfolio and monetary policy shocks playing greater roles. We also find evidence shocks, results indicate that comovement in real house prices is due to the combined effects of favourable and unfavourable structural shocks emanating from different sectors of the economy, of significant feedbacks from the housing sector to the real economy which theoretically channel through the wealth and /or collateral and balance sheet effects on consumption and investment, respectively. The second chapter implements a Panel Vector Autoregression (PVAR) approach on provincial level data to analyse the role of house prices in determining the dynamic behaviour of consumption. Unlike individual regression, this approach accounts for individual heterogeneities characteristic of provincial housing markets. Based on the standard recursive identification, we find that house prices exhibit an asymmetric effect on consumption: a positive shock to house price growth has a positive and significant effect on consumption, while the negative impact of an anticipated house price causes an insignificant reduction in consumption. Because consumption is a significant component of Gross Domestic Product (GDP), the effect of house prices on consumption serves as a key link between the housing market and economic activity. The third chapter, therefore, exploits panel time series methods to examine the impact of house price changes on economic growth across provinces. This framework offers a variety of tools designed to address econometric issues such as heterogeneity, endogeneity and spatial effects which have been found to be prominent in regional housing markets. Specifically, Fixed effect (FE) and Random coefficient (RC) models are used to address the issue of heterogeneity. The potential endogeneity is accounted for using SYSTEM-Generalised Method of Moments (SYS-GMM) while the Feasible Generalised Least Squared (FGLS) and the Seemingly Unrelated Regression (SUR) are used to control for spatial effects. Accounting for these above issues leads to a significant effect of house price changes on provincial economic growth in South Africa. Since house prices affect the business cycle, monetary policy might not be neutral to house price movements. Moreover, one may expect asymmetric response of monetary policy to house price shocks giving the boom/bust nature of house price dynamics. In light of these considerations, the fourth chapter links South African housing market dynamics to the interest rate setting behaviour by relying on Markov-Switching Vector Autoregressive (MS-VAR). This technique allows identifying the bull and bear regimes in the South African housing market and therefore helps examining asymmetries in the impact of monetary policy shocks on the house prices during bull and bear regimes. The impact of the monetary policy on house prices is found to be larger in the bear regime than in the bull regime; indicating the role of information asymmetry in reinforcing the financial constraint of economic agent. Unsurprisingly, monetary reaction to a positive house price shock is found to be stronger in the bull regime. This suggests that central banker are more concerned in bull regime given the potential crisis related to the subsequent bust in house prices bubbles which are more prominent in bull markets. Finally, changes in house prices induce an adjustment of consumption and investment decisions which could be reflected as a trade surplus or deficit. The fifth chapter characterises the dynamic relationship between house prices and the trade balance based on a Bayesian Vector Autoregressive (BVAR) approach with sign restrictions. The results indicate that 1 percent decline in house prices can improve the trade balance by 0.2 percent; suggesting that house prices represent an additional instrument for trade-balance adjustment besides the traditional exchange rate channel. Further, we find that the contribution of house price shocks to the historical path of the trade balance is less prominent in 2000s; possibly substantiating the effectiveness in the conduct of South African monetary policy, which has been shown to be incorporating house price movements in its interest rate setting behaviour.Thesis (PhD)--University of Pretoria, 2013.http://hdl.handle.net/2263/31859hb2013Economicsunrestricte

Segmentation d'images et suivi d'objets en vidéos approches par estimation, sélection de caractéristiques et contours actifs

Cette thèse aborde deux problèmes parmi les plus importants et les plus complexes dans la vision artificielle, qui sont la segmentation d'images et le suivi d'objets dans les vidéos. Nous proposons plusieurs approches, traitant de ces deux problèmes, qui sont basées sur la modélisation variationnelle (contours actifs) et statistique. Ces approches ont pour but de surmonter différentes limites théoriques et pratiques (algorithmiques) de ces deux problèmes. En premier lieu, nous abordons le problème d'automatisation de la segmentation par contours actifs"ensembles de niveaux", et sa généralisation pour le cas de plusieurs régions. Pour cela, un modèle permettant d'estimer l'information de régions de manière automatique, et adaptative au contenu de l'image, est proposé. Ce modèle n'utilise aucune information a priori sur les régions, et traite également les images de couleur et de texture, avec un nombre arbitraire de régions. Nous introduisons ensuite une approche statistique pour estimer et intégrer la pertinence des caractéristiques et la sémantique dans la segmentation d'objets d'intérêt. En deuxième lieu, nous abordons le problème du suivi d'objets dans les vidéos en utilisant les contours actifs. Nous proposons pour cela deux modèles différents. Le premier suppose que les propriétés photométriques des objets suivis sont invariantes dans le temps, mais le modèle est capable de suivre des objets en présence de bruit, et au milieu de fonds de vidéos non-statiques et encombrés. Ceci est réalisé grâce à l'intégration de l'information de régions, de frontières et de formes des objets suivis. Le deuxième modèle permet de prendre en charge les variations photométriques des objets suivis, en utilisant un modèle statistique adaptatif à l'apparence de ces derniers. Finalement, nous proposons un nouveau modèle statistique, basé sur la Gaussienne généralisée, pour une représentation efficace de données bruitées et de grandes dimensions en segmentation. Ce modèle est utilisé pour assurer la robustesse de la segmentation des images de couleur contenant du bruit, ainsi que des objets en mouvement dans les vidéos (acquises par des caméras statiques) contenant de l'ombrage et/ou des changements soudains d'illumination

Investigation of a dynamic economic system : the specification of Australian beef cattle supply

This thesis is concerned with investigating the practical determination of an appropriate specification for a dynamic economic system, that of Australian beef cattle supply. As such, it may be logically divided into four parts. Part 1, consists of Chapters I, II and III, which are necessary and lengthy scene-setting Chapters in various guises. Chapter I contains a general introduction to practical specification searches and an overview of the thesis. Chapter II and related Appendices develop the chosen application through all its component stages of economic specification, data considerations and econometric specification, introducing some new developments. Chapter III introduces the major quantitative aspects of the specification search for later development. Part 2, made up of Chapters IV, V and VI, concerns those quantitative components that utilise available data and contain the main technical developments of the thesis. Chapter IV considers the diagnostic testing component, especially those related to data questions both individually and jointly. Chapter V considers the model selection component, especially in relation to the comprehensive model made up of individual (non-nested) models. Chapter VI develops extensions to both the components considered that are relevant to the chosen application. Part 3, comprises Chapters VII and VIII, and contains applications of the earlier developments. Chapter VII specifically applies some of the extended techniques that were developed to an empirical example suited to their illustration. Chapter VIII applies the procedures in general to the chosen application that was developed earlier. Part 4, consists of Chapter IX which contains a summary incorporating an overall strategy for specifications searches and brief concluding comments