3-Regime symmetric STAR modeling and exchange rate reversion

The breakdown of the Bretton Woods system and the adoption of generalized oating exchange rates ushered in a new era of exchange rate volatility and uncer- tainty. This increased volatility lead economists to search for economic models able to describe observed exchange rate behavior. In the present paper we propose more general STAR transition functions which encompass both threshold nonlinearity and asymmetric e¤ects. Our framework allows for a gradual adjustment from one regime to another, and considers threshold e¤ects by encompassing other existing models, such as TAR models. We apply our methodology to three di¤erent exchange rate data-sets, one for developing countries, and o¢ cial nominal exchange rates, the sec- ond emerging market economies using black market exchange rates and the third for OECD economies.

Object recognition for autonomous objects: comparison of two approaches

Report for the scientific sojourn at the Swiss Federal Institute of Technology Zurich, Switzerland, between September and December 2007. In order to make robots useful assistants for our everyday life, the ability to learn and recognize objects is of essential importance. However, object recognition in real scenes is one of the most challenging problems in computer vision, as it is necessary to deal with difficulties. Furthermore, in mobile robotics a new challenge is added to the list: computational complexity. In a dynamic world, information about the objects in the scene can become obsolete before it is ready to be used if the detection algorithm is not fast enough. Two recent object recognition techniques have achieved notable results: the constellation approach proposed by Lowe and the bag of words approach proposed by Nistér and Stewénius. The Lowe constellation approach is the one currently being used in the robot localization project of the COGNIRON project. This report is divided in two main sections. The first section is devoted to briefly review the currently used object recognition system, the Lowe approach, and bring to light the drawbacks found for object recognition in the context of indoor mobile robot navigation. Additionally the proposed improvements for the algorithm are described. In the second section the alternative bag of words method is reviewed, as well as several experiments conducted to evaluate its performance with our own object databases. Furthermore, some modifications to the original algorithm to make it suitable for object detection in unsegmented images are proposed.

Technical Appendix-3-Regime asymmetric STAR modeling and exchange rate reversion

The breakdown of the Bretton Woods system and the adoption of generalized oating exchange rates ushered in a new era of exchange rate volatility and uncer- tainty. This increased volatility lead economists to search for economic models able to describe observed exchange rate behavior. The present is a technical Appendix to Cerrato et al. (2009) and presents detailed simulations of the proposed methodology and additional empirical results.

Body mass index, cigarette smoking, and alcohol consumption and cancers of the oral cavity, pharynx, and larynx: modeling odds ratios in pooled case-control data.

Odds ratios for head and neck cancer increase with greater cigarette and alcohol use and lower body mass index (BMI; weight (kg)/height(2) (m(2))). Using data from the International Head and Neck Cancer Epidemiology Consortium, the authors conducted a formal analysis of BMI as a modifier of smoking- and alcohol-related effects. Analysis of never and current smokers included 6,333 cases, while analysis of never drinkers and consumers of < or =10 drinks/day included 8,452 cases. There were 8,000 or more controls, depending on the analysis. Odds ratios for all sites increased with lower BMI, greater smoking, and greater drinking. In polytomous regression, odds ratios for BMI (P = 0.65), smoking (P = 0.52), and drinking (P = 0.73) were homogeneous for oral cavity and pharyngeal cancers. Odds ratios for BMI and drinking were greater for oral cavity/pharyngeal cancer (P < 0.01), while smoking odds ratios were greater for laryngeal cancer (P < 0.01). Lower BMI enhanced smoking- and drinking-related odds ratios for oral cavity/pharyngeal cancer (P < 0.01), while BMI did not modify smoking and drinking odds ratios for laryngeal cancer. The increased odds ratios for all sites with low BMI may suggest related carcinogenic mechanisms; however, BMI modification of smoking and drinking odds ratios for cancer of the oral cavity/pharynx but not larynx cancer suggests additional factors specific to oral cavity/pharynx cancer.

Modeling U.S. Inflation Dynamics: A Bayesian Nonparametric Approach

This paper uses an infinite hidden Markov model (IIHMM) to analyze U.S. inflation dynamics with a particular focus on the persistence of inflation. The IHMM is a Bayesian nonparametric approach to modeling structural breaks. It allows for an unknown number of breakpoints and is a flexible and attractive alternative to existing methods. We found a clear structural break during the recent financial crisis. Prior to that, inflation persistence was high and fairly constant.

Multilevel Modelling with Spatial Effects

In multilevel modelling, interest in modeling the nested structure of hierarchical data has been accompanied by increasing attention to different forms of spatial interactions across different levels of the hierarchy. Neglecting such interactions is likely to create problems of inference, which typically assumes independence. In this paper we review approaches to multilevel modelling with spatial effects, and attempt to connect the two literatures, discussing the advantages and limitations of various approaches.

Fusion of Multi-Atlas Segmentations with Spatial Distribution Modeling

In recent years, multi-atlas fusion methods have gainedsignificant attention in medical image segmentation. Inthis paper, we propose a general Markov Random Field(MRF) based framework that can perform edge-preservingsmoothing of the labels at the time of fusing the labelsitself. More specifically, we formulate the label fusionproblem with MRF-based neighborhood priors, as an energyminimization problem containing a unary data term and apairwise smoothness term. We present how the existingfusion methods like majority voting, global weightedvoting and local weighted voting methods can be reframedto profit from the proposed framework, for generatingmore accurate segmentations as well as more contiguoussegmentations by getting rid of holes and islands. Theproposed framework is evaluated for segmenting lymphnodes in 3D head and neck CT images. A comparison ofvarious fusion algorithms is also presented.

Time Horizons And Smoothing In The Bank Of England’s Reaction Function: The Contrast Between The Standard GMM And Ex Ante Forecast Approaches

The monetary policy reaction function of the Bank of England is estimated by the standard GMM approach and the ex-ante forecast method developed by Goodhart (2005), with particular attention to the horizons for inflation and output at which each approach gives the best fit. The horizons for the ex-ante approach are much closer to what is implied by the Bank’s view of the transmission mechanism, while the GMM approach produces an implausibly slow adjustment of the interest rate, and suffers from a weak instruments problem. These findings suggest a strong preference for the ex-ante approach.

Time Horizons And Smoothing In The Bank Of England’s Reaction Function: The Contrast Between The Standard GMM And Ex Ante Forecast Approaches

The monetary policy reaction function of the Bank of England is estimated by the standard GMM approach and the ex-ante forecast method developed by Goodhart (2005), with particular attention to the horizons for inflation and output at which each approach gives the best fit. The horizons for the ex-ante approach are much closer to what is implied by the Bank’s view of the transmission mechanism, while the GMM approach produces an implausibly slow adjustment of the interest rate, and suffers from a weak instruments problem. These findings suggest a strong preference for the ex-ante approach.

Sparse regularization for fiber ODF reconstruction: from the suboptimality of ℓ2 and ℓ1 priors to ℓ0.

Diffusion MRI is a well established imaging modality providing a powerful way to probe the structure of the white matter non-invasively. Despite its potential, the intrinsic long scan times of these sequences have hampered their use in clinical practice. For this reason, a large variety of methods have been recently proposed to shorten the acquisition times. Among them, spherical deconvolution approaches have gained a lot of interest for their ability to reliably recover the intra-voxel fiber configuration with a relatively small number of data samples. To overcome the intrinsic instabilities of deconvolution, these methods use regularization schemes generally based on the assumption that the fiber orientation distribution (FOD) to be recovered in each voxel is sparse. The well known Constrained Spherical Deconvolution (CSD) approach resorts to Tikhonov regularization, based on an ℓ(2)-norm prior, which promotes a weak version of sparsity. Also, in the last few years compressed sensing has been advocated to further accelerate the acquisitions and ℓ(1)-norm minimization is generally employed as a means to promote sparsity in the recovered FODs. In this paper, we provide evidence that the use of an ℓ(1)-norm prior to regularize this class of problems is somewhat inconsistent with the fact that the fiber compartments all sum up to unity. To overcome this ℓ(1) inconsistency while simultaneously exploiting sparsity more optimally than through an ℓ(2) prior, we reformulate the reconstruction problem as a constrained formulation between a data term and a sparsity prior consisting in an explicit bound on the ℓ(0)norm of the FOD, i.e. on the number of fibers. The method has been tested both on synthetic and real data. Experimental results show that the proposed ℓ(0) formulation significantly reduces modeling errors compared to the state-of-the-art ℓ(2) and ℓ(1) regularization approaches.

Modeling Dependence Structure and Forecasting Portfolio Value-at-Risk with Dynamic Copulas

We study the asymmetric and dynamic dependence between financial assets and demonstrate, from the perspective of risk management, the economic significance of dynamic copula models. First, we construct stock and currency portfolios sorted on different characteristics (ex ante beta, coskewness, cokurtosis and order flows), and find substantial evidence of dynamic evolution between the high beta (respectively, coskewness, cokurtosis and order flow) portfolios and the low beta (coskewness, cokurtosis and order flow) portfolios. Second, using three different dependence measures, we show the presence of asymmetric dependence between these characteristic-sorted portfolios. Third, we use a dynamic copula framework based on Creal et al. (2013) and Patton (2012) to forecast the portfolio Value-at-Risk of long-short (high minus low) equity and FX portfolios. We use several widely used univariate and multivariate VaR models for the purpose of comparison. Backtesting our methodology, we find that the asymmetric dynamic copula models provide more accurate forecasts, in general, and, in particular, perform much better during the recent financial crises, indicating the economic significance of incorporating dynamic and asymmetric dependence in risk management.

Profile of a serial killer: cellular and molecular approaches to study individual cytotoxic T-cells following therapeutic vaccination.

T-cell vaccination may prevent or treat cancer and infectious diseases, but further progress is required to increase clinical efficacy. Step-by-step improvements of T-cell vaccination in phase I/II clinical studies combined with very detailed analysis of T-cell responses at the single cell level are the strategy of choice for the identification of the most promising vaccine candidates for testing in subsequent large-scale phase III clinical trials. Major aims are to fully identify the most efficient T-cells in anticancer therapy, to characterize their TCRs, and to pinpoint the mechanisms of T-cell recruitment and function in well-defined clinical situations. Here we discuss novel strategies for the assessment of human T-cell responses, revealing in part unprecedented insight into T-cell biology and novel structural principles that govern TCR-pMHC recognition. Together, the described approaches advance our knowledge of T-cell mediated-protection from human diseases.

Optimisation of antiretroviral therapy : pharmacokinetic and pharmacogenetic approaches

Les progrès de la thérapie antirétrovirale ont transformé l'infection par le VIH d'une condition inévitablement fatale à une maladie chronique. En dépit de ce succès, l'échec thérapeutique et la toxicité médicamenteuse restent fréquents. Une réponse inadéquate au traitement est clairement multifactorielle et une individualisation de la posologie des médicaments qui se baserait sur les facteurs démographiques et génétiques des patients et sur les taux sanguins totaux, libres et/ou cellulaires des médicaments pourrait améliorer à la fois l'efficacité et la tolérance de la thérapie, cette dernière étant certainement un enjeu majeur pour un traitement qui se prend à vie.L'objectif global de cette thèse était de mieux comprendre les facteurs pharmacocinétiques (PK) et pharmacogénétiques (PG) influençant l'exposition aux médicaments antirétroviraux (ARVs) nous offrant ainsi une base rationnelle pour l'optimisation du traitement antiviral et pour l'ajustement posologique des médicaments chez les patients VIH-positifs. Une thérapie antirétrovirale adaptée au patient est susceptible d'augmenter la probabilité d'efficacité et de tolérance à ce traitement, permettant ainsi une meilleure compliance à long terme, et réduisant le risque d'émergence de résistance et d'échec thérapeutique.A cet effet, des méthodes de quantification des concentrations plasmatiques totales, libres et cellulaires des ARVs ainsi que de certains de leurs métabolites ont été développées et validées en utilisant la chromatographie liquide coupée à la spectrométrie de masse en tandem. Ces méthodes ont été appliquées pour la surveillance des taux d'ARVs dans diverses populations de patients HIV-positifs. Une étude clinique a été initiée dans le cadre de l'étude VIH Suisse de cohorte mère-enfant afin de déterminer si la grossesse influence la cinétique des ARVs. Les concentrations totales et libres du lopînavir, de l'atazanavir et de la névirapine ont été déterminées chez les femmes enceintes suivies pendant leur grossesse, et celles-ci ont été trouvées non influencées de manière cliniquement significative par la grossesse. Un ajustement posologique de ces ARVs n'est donc pas nécessaire chez les femmes enceintes. Lors d'une petite étude chez des patients HIV- positifs expérimentés, la corrélation entre l'exposition cellulaire et plasmatique des nouveaux ARVs, notamment le raltégravir, a été déterminée. Une bonne corrélation a été obtenue entre taux plasmatiques et cellulaires de raltégravir, suggérant que la surveillance des taux totaux est un substitut satisfaisant. Cependant, une importante variabilité inter¬patient a été observée dans les ratios d'accumulation cellulaire du raltégravir, ce qui devrait encourager des investigations supplémentaires chez les patients en échec sous ce traitement. L'efficacité du suivi thérapeutique des médicaments (TDM) pour l'adaptation des taux d'efavirenz chez des patients avec des concentrations au-dessus de la cible thérapeutique recommandée a été évaluée lors d'une étude prospective. L'adaptation des doses d'efavirenz basée sur le TDM s'est montrée efficace et sûre, soutenant l'utilisation du TDM chez les patients avec concentrations hors cible thérapeutique. L'impact des polymorphismes génétiques des cytochromes P450 (CYP) 2B6, 2A6 et 3A4/5 sur la pharmacocinétique de l'efavirenz et de ces métabolites a été étudié : un modèle de PK de population intégrant les covariats génétiques et démographiques a été construit. Les variations génétiques fonctionnelles dans les voies de métabolisation principales (CYP2B6) et accessoires {CYP2A6et 3A4/S) de l'efavirenz ont un impact sur sa disposition, et peuvent mener à des expositions extrêmes au médicament. Un? ajustement des doses guidé par le TDM est donc recommandé chez ces patients, en accord avec les polymorphismes génétiques.Ainsi, nous avons démonté qu'en utilisant une approche globale tenant compte à la fois des facteurs PK et PG influençant l'exposition aux ARVs chez les patients infectés, il est possible, si nécessaire, d'individualiser la thérapie antirétrovirale dans des situations diverses. L'optimisation du traitement antirétroviral contribue vraisemblablement à une meilleure efficacité thérapeutique à iong terme tout en réduisant la survenue d'effets indésirables.Résumé grand publicOptimisation de la thérapie antirétrovirale: approches pharmacocinétiques et pharmacogénétiquesLes progrès effectués dans le traitement de l'infection par le virus de llmmunodéficienoe humaine acquise (VIH) ont permis de transformer une affection mortelle en une maladie chronique traitable avec des médicaments de plus en plus efficaces. Malgré ce succès, un certain nombre de patients ne répondent pas de façon optimale à leur traitement etyou souffrent d'effets indésirables médicamenteux entraînant de fréquentes modifications dans leur thérapie. Il a été possible de mettre en évidence que l'efficacité d'un traitement antirétroviral est dans la plupart des cas corrélée aux concentrations de médicaments mesurées dans le sang des patients. Cependant, le virus se réplique dans la cellule, et seule la fraction des médicaments non liée aux protéines du plasma sanguin peut entrer dans la cellule et exercer l'activité antirétrovirale au niveau cellulaire. Il existe par ailleurs une importante variabilité des concentrations sanguines de médicament chez des patients prenant pourtant la même dose de médicament. Cette variabilité peut être due à des facteurs démographiques et/ou génétiques susceptibles d'influencer la réponse au traitement antirétroviral.Cette thèse a eu pour objectif de mieux comprendre les facteurs pharmacologiques et génétiques influençant l'efficacité et ta toxicité des médicaments antirétroviraux, dans le but d'individualiser la thérapie antivirale et d'améliorer le suivi des patients HIV-positifs.A cet effet, des méthodes de dosage très sensibles ont été développées pour permettre la quantification des médicaments antirétroviraux dans le sang et les cellules. Ces méthodes analytiques ont été appliquées dans le cadre de diverses études cliniques réalisées avec des patients. Une des études cliniques a recherché s'il y avait un impact des changements physiologiques liés à la grossesse sur les concentrations des médicaments antirétroviraux. Nous avons ainsi pu démontrer que la grossesse n'influençait pas de façon cliniquement significative le devenir des médicaments antirétroviraux chez les femmes enceintes HIV- positives. La posologie de médicaments ne devrait donc pas être modifiée dans cette population de patientes. Par ailleurs, d'autres études ont portés sur les variations génétiques des patients influençant l'activité enzymatique des protéines impliquées dans le métabolisme des médicaments antirétroviraux. Nous avons également étudié l'utilité d'une surveillance des concentrations de médicament (suivi thérapeutique) dans le sang des patients pour l'individualisation des traitements antiviraux. Il a été possible de mettre en évidence des relations significatives entre l'exposition aux médicaments antirétroviraux et l'existence chez les patients de certaines variations génétiques. Nos analyses ont également permis d'étudier les relations entre les concentrations dans le sang des patients et les taux mesurés dans les cellules où le virus HIV se réplique. De plus, la mesure des taux sanguins de médicaments antirétroviraux et leur interprétation a permis d'ajuster la posologie de médicaments chez les patients de façon efficace et sûre.Ainsi, la complémentarité des connaissances pharmacologiques, génétiques et virales s'inscrit dans l'optique d'une stratégie globale de prise en charge du patient et vise à l'individualisation de la thérapie antirétrovirale en fonction des caractéristiques propres de chaque individu. Cette approche contribue ainsi à l'optimisation du traitement antirétroviral dans la perspective d'un succès du traitement à long terme tout en réduisant la probabilité des effets indésirables rencontrés. - The improvement in antirétroviral therapy has transformed HIV infection from an inevitably fatal condition to a chronic, manageable disease. However, treatment failure and drug toxicity are frequent. Inadequate response to treatment is clearly multifactorial and, therefore, dosage individualisation based on demographic factors, genetic markers and measurement of total, free and/or cellular drug level may increase both drug efficacy and tolerability. Drug tolerability is certainly a major issue for a treatment that must be taken indefinitely.The global objective of this thesis aimed at increasing our current understanding of pharmacokinetic (PK) and pharmacogenetic (PG) factors influencing the exposition to antirétroviral drugs (ARVs) in HIV-positive patients. In turn, this should provide us with a rational basis for antiviral treatment optimisation and drug dosage adjustment in HIV- positive patients. Patient's tailored antirétroviral regimen is likely to enhance treatment effectiveness and tolerability, enabling a better compliance over time, and hence reducing the probability of emergence of viral resistance and treatment failure.To that endeavour, analytical methods for the measurement of total plasma, free and cellular concentrations of ARVs and some of their metabolites have been developed and validated using liquid chromatography coupled with tandem mass spectrometry. These assays have been applied for the monitoring of ARVs levels in various populations of HIV- positive patients. A clinical study has been initiated within the frame of the Mother and Child Swiss HIV Cohort Study to determine whether pregnancy influences the exposition to ARVs. Free and total plasma concentrations of lopinavir, atazanavir and nevirapine have been determined in pregnant women followed during the course of pregnancy, and were found not influenced to a clinically significant extent by pregnancy. Dosage adjustment for these drugs is therefore not required in pregnant women. In a study in treatment- experienced HIV-positive patients, the correlation between cellular and total plasma exposure to new antirétroviral drugs, notably the HIV integrase inhibitor raltegravir, has been determined. A good correlation was obtained between total and cellular levels of raltegravir, suggesting that monitoring of total levels are a satisfactory. However, significant inter-patient variability was observed in raltegravir cell accumulation which should prompt further investigations in patients failing under an integrase inhibitor-based regimen. The effectiveness of therapeutic drug monitoring (TDM) to guide efavirenz dose reduction in patients having concentrations above the recommended therapeutic range was evaluated in a prospective study. TDM-guided dosage adjustment of efavirenz was found feasible and safe, supporting the use of TDM in patients with efavirenz concentrations above therapeutic target. The impact of genetic polymorphisms of cytochromes P450 (CYP) 2B6, 2A6 and 3A4/5 on the PK of efavirenz and its metabolites was studied: a population PK model was built integrating both genetic and demographic covariates. Functional genetic variations in main (CYP2B6) and accessory (2A6, 3A4/5) metabolic pathways of efavirenz have an impact on efavirenz disposition, and may lead to extreme drug exposures. Dosage adjustment guided by TDM is thus required in those patients, according to the pharmacogenetic polymorphism.Thus, we have demonstrated, using a comprehensive approach taking into account both PK and PG factors influencing ARVs exposure in HIV-infected patients, the feasibility of individualising antirétroviral therapy in various situations. Antiviral treatment optimisation is likely to increase long-term treatment success while reducing the occurrence of adverse drug reactions.

Modeling Dependence Structure and Forecasting Market Risk with Dynamic Asymmetric Copula

We investigate the dynamic and asymmetric dependence structure between equity portfolios from the US and UK. We demonstrate the statistical significance of dynamic asymmetric copula models in modelling and forecasting market risk. First, we construct “high-minus-low" equity portfolios sorted on beta, coskewness, and cokurtosis. We find substantial evidence of dynamic and asymmetric dependence between characteristic-sorted portfolios. Second, we consider a dynamic asymmetric copula model by combining the generalized hyperbolic skewed t copula with the generalized autoregressive score (GAS) model to capture both the multivariate non-normality and the dynamic and asymmetric dependence between equity portfolios. We demonstrate its usefulness by evaluating the forecasting performance of Value-at-Risk and Expected Shortfall for the high-minus-low portfolios. From back-testing, e find consistent and robust evidence that our dynamic asymmetric copula model provides the most accurate forecasts, indicating the importance of incorporating the dynamic and asymmetric dependence structure in risk management.