Reducible Diffusions with Time-Varying Transformations with Application to Short-Term Interest Rates

Reducible diffusions (RDs) are nonlinear transformations of analytically solvable Basic Diffusions (BDs). Hence, by construction RDs are analytically tractable and flexible diffusion processes. Existing literature on RDs has mostly focused on time-homogeneous transformations, which to a significant extent fail to explore the full potential of RDs from both theoretical and practical points of view. In this paper, we propose flexible and economically justifiable time variations to the transformations of RDs. Concentrating on the Constant Elasticity Variance (CEV) RDs, we consider nonlinear dynamics for our time-varying transformations with both deterministic and stochastic designs. Such time variations can greatly enhance the flexibility of RDs while maintaining sufficient tractability of the resulting models. In the meantime, our modeling approach enjoys the benefits of classical inferential techniques such as the Maximum Likelihood (ML). Our application to the UK and the US short-term interest rates suggests that from an empirical point of view time-varying transformations are highly relevant and statistically significant. We expect that the proposed models can describe more truthfully the dynamic time-varying behavior of economic and financial variables and potentially improve out-of-sample forecasts significantly.

Sedentary behaviour and physical activity in bronchiectasis: a cross-sectional study

BACKGROUND: The impact of bronchiectasis on sedentary behaviour and physical activity is unknown. It is important to explore this to identify the need for physical activity interventions and how to tailor interventions to this patient population. We aimed to explore the patterns and correlates of sedentary behaviour and physical activity in bronchiectasis.

METHODS: Physical activity was assessed in 63 patients with bronchiectasis using an ActiGraph GT3X+ accelerometer over seven days. Patients completed: questionnaires on health-related quality-of-life and attitudes to physical activity (questions based on an adaption of the transtheoretical model (TTM) of behaviour change); spirometry; and the modified shuttle test (MST). Multiple linear regression analysis using forward selection based on likelihood ratio statistics explored the correlates of sedentary behaviour and physical activity dimensions. Between-group analysis using independent sample t-tests were used to explore differences for selected variables.

RESULTS: Fifty-five patients had complete datasets. Average daily time, mean(standard deviation) spent in sedentary behaviour was 634(77)mins, light-lifestyle physical activity was 207(63)mins and moderate-vigorous physical activity (MVPA) was 25(20)mins. Only 11% of patients met recommended guidelines. Forced expiratory volume in one-second percentage predicted (FEV1% predicted) and disease severity were not correlates of sedentary behaviour or physical activity. For sedentary behaviour, decisional balance 'pros' score was the only correlate. Performance on the MST was the strongest correlate of physical activity. In addition to the MST, there were other important correlate variables for MVPA accumulated in ≥10-minute bouts (QOL-B Social Functioning) and for activity energy expenditure (Body Mass Index and QOL-B Respiratory Symptoms).

CONCLUSIONS: Patients with bronchiectasis demonstrated a largely inactive lifestyle and few met the recommended physical activity guidelines. Exercise capacity was the strongest correlate of physical activity, and dimensions of the QOL-B were also important. FEV1% predicted and disease severity were not correlates of sedentary behaviour or physical activity. The inclusion of a range of physical activity dimensions could facilitate in-depth exploration of patterns of physical activity. This study demonstrates the need for interventions targeted at reducing sedentary behaviour and increasing physical activity, and provides information to tailor interventions to the bronchiectasis population.

Bereavement After Informal Caregiving: Assessing Mental Health Burden Using Linked Population Data

Methods. We linked prescription records for antidepressant and anxiolytic drugs to characteristics and life-event data of members of the Northern Ireland Longitudinal Study (n = 317 264). Using a case-control design, we fitted logistic regression models, stratified by age, to model relative likelihood of mental health problems, using the proxy measures of mental health–related prescription.

Results. Both caregivers and bereaved individuals were estimated to be at between 20% and 50% greater risk for mental health problems than noncaregivers in similar circumstances (for bereaved working-age caregivers, odds ratio = 1.41; 95% confidence interval = 1.27, 1.56). For older people, there was no evidence of additional risk to bereaved caregivers, though there was for working-age people. Older people appeared to recover more quickly from caregiver bereavement.

Simultaneous biosorption of methylene blue and trivalent chromium onto olive stone

In this work, olive stone (OS) was utilized to investigate its capacity as biosorbent for methylene blue (MB) and Cr(III), which are usually present in textile industry effluents. Equilibrium and kinetic experiments were performed in batch experiments. The biosorption process followed pseudo-second-order kinetics. The equilibrium data were fitted with several models, but Langmuir and Sips models best reproduced the experimental results. Maximum biosorption capacities were 3.296 mg/g (0.0116 mmol/g) and 4.990 mg/g (0.0960 mmol/g) for MB and Cr(III), respectively. Several operation variables, such as
biosorbent mass, flow rate, and initial concentration on the removal of dye and metal, were evaluated in column system. The removal efficiency improved as OS mass increased and decreased when flow rate and initial concentration increased. Also, MB uptake was substantially decreased by increasing the initial concentration of Cr(III), ranging from 6.09 to 2.75 mg/g. These results show that the presence of Cr(III) significantly modifies the biosorption capacity of MB by the OS. These results suggest that OS is a potential low-cost food industry waste for textile industry wastewater treatment.

Estimação robusta em modelos lineares de equações simultâneas

Os Modelos de Equações Simultâneas (SEM) são modelos estatísticos com muita tradição em estudos de Econometria, uma vez que permitem representar e estudar uma vasta gama de processos económicos. Os estimadores mais usados em SEM resultam da aplicação do Método dos Mínimos Quadrados ou do Método da Máxima Verosimilhança, os quais não são robustos. Em Maronna e Yohai (1997), os autores propõem formas de “robustificar” esses estimadores. Um outro método de estimação com interesse nestes modelos é o Método dos Momentos Generalizado (GMM), o qual também conduz a estimadores não robustos. Estimadores que sofrem de falta de robustez são muito inconvenientes uma vez que podem conduzir a resultados enganadores quando são violadas as hipóteses subjacentes ao modelo assumido. Os estimadores robustos são de grande valor, em particular quando os modelos em estudo são complexos, como é o caso dos SEM. O principal objectivo desta investigação foi o de procurar tais estimadores tendo-se construído um estimador robusto a que se deu o nome de GMMOGK. Trata-se de uma versão robusta do estimador GMM. Para avaliar o desempenho do novo estimador foi feito um adequado estudo de simulação e foi também feita a aplicação do estimador a um conjunto de dados reais. O estimador robusto tem um bom desempenho nos modelos heterocedásticos considerados e, nessas condições, comporta-se melhor do que os estimadores não robustos usados no estudo. Contudo, quando a análise é feita em cada equação separadamente, a especificidade de cada equação individual e a estrutura de dependência do sistema são dois aspectos que influenciam o desempenho do estimador, tal como acontece com os estimadores usuais. Para enquadrar a investigação, o texto inclui uma revisão de aspectos essenciais dos SEM, o seu papel em Econometria, os principais métodos de estimação, com particular ênfase no GMM, e uma curta introdução à estimação robusta.

Optimal alarms systems and its application to financial time series

This thesis focuses on the application of optimal alarm systems to non linear time series models. The most common classes of models in the analysis of real-valued and integer-valued time series are described. The construction of optimal alarm systems is covered and its applications explored. Considering models with conditional heteroscedasticity, particular attention is given to the Fractionally Integrated Asymmetric Power ARCH, FIAPARCH(p; d; q) model and an optimal alarm system is implemented, following both classical and Bayesian methodologies. Taking into consideration the particular characteristics of the APARCH(p; q) representation for financial time series, the introduction of a possible counterpart for modelling time series of counts is proposed: the INteger-valued Asymmetric Power ARCH, INAPARCH(p; q). The probabilistic properties of the INAPARCH(1; 1) model are comprehensively studied, the conditional maximum likelihood (ML) estimation method is applied and the asymptotic properties of the conditional ML estimator are obtained. The final part of the work consists on the implementation of an optimal alarm system to the INAPARCH(1; 1) model. An application is presented to real data series.

Parallel decoding of turbo codes using multi-point trellis termination and collision-free interleavers

The UMTS turbo encoder is composed of parallel concatenation of two Recursive Systematic Convolutional (RSC) encoders which start and end at a known state. This trellis termination directly affects the performance of turbo codes. This paper presents performance analysis of multi-point trellis termination of turbo codes which is to terminate RSC encoders at more than one point of the current frame while keeping the interleaver length the same. For long interleaver lengths, this approach provides dividing a data frame into sub-frames which can be treated as independent blocks. A novel decoding architecture using multi-point trellis termination and collision-free interleavers is presented. Collision-free interleavers are used to solve memory collision problems encountered by parallel decoding of turbo codes. The proposed parallel decoding architecture reduces the decoding delay caused by the iterative nature and forward-backward metric computations of turbo decoding algorithms. Our simulations verified that this turbo encoding and decoding scheme shows Bit Error Rate (BER) performance very close to that of the UMTS turbo coding while providing almost %50 time saving for the 2-point termination and %80 time saving for the 5-point termination.

A probabilistic methodology for distributed generation location in isolated electrical service area

Distributed generation unlike centralized electrical generation aims to generate electrical energy on small scale as near as possible to load centers, interchanging electric power with the network. This work presents a probabilistic methodology conceived to assist the electric system planning engineers in the selection of the distributed generation location, taking into account the hourly load changes or the daily load cycle. The hourly load centers, for each of the different hourly load scenarios, are calculated deterministically. These location points, properly weighted according to their load magnitude, are used to calculate the best fit probability distribution. This distribution is used to determine the maximum likelihood perimeter of the area where each source distributed generation point should preferably be located by the planning engineers. This takes into account, for example, the availability and the cost of the land lots, which are factors of special relevance in urban areas, as well as several obstacles important for the final selection of the candidates of the distributed generation points. The proposed methodology has been applied to a real case, assuming three different bivariate probability distributions: the Gaussian distribution, a bivariate version of Freund’s exponential distribution and the Weibull probability distribution. The methodology algorithm has been programmed in MATLAB. Results are presented and discussed for the application of the methodology to a realistic case and demonstrate the ability of the proposed methodology for efficiently handling the determination of the best location of the distributed generation and their corresponding distribution networks.

Extremum estimators and stochastic optimization methods

Submitted in partial fulfillment for the Requirements for the Degree of PhD in Mathematics, in the Speciality of Statistics in the Faculdade de Ciências e Tecnologia

The evolutionary history of the CD209 (DC-SIGN) family in humans and non-human primates

The CD209 gene family that encodes C-type lectins in primates includes CD209 (DC-SIGN), CD209L (L-SIGN) and CD209L2. Understanding the evolution of these genes can help understand the duplication events generating this family, the process leading to the repeated neck region and identify protein domains under selective pressure. We compiled sequences from 14 primates representing 40 million years of evolution and from three non-primate mammal species. Phylogenetic analyses used Bayesian inference, and nucleotide substitutional patterns were assessed by codon-based maximum likelihood. Analyses suggest that CD209 genes emerged from a first duplication event in the common ancestor of anthropoids, yielding CD209L2 and an ancestral CD209 gene, which, in turn, duplicated in the common Old World primate ancestor, giving rise to CD209L and CD209. K(A)/K(S) values averaged over the entire tree were 0.43 (CD209), 0.52 (CD209L) and 0.35 (CD209L2), consistent with overall signatures of purifying selection. We also assessed the Toll-like receptor (TLR) gene family, which shares with CD209 genes a common profile of evolutionary constraint. The general feature of purifying selection of CD209 genes, despite an apparent redundancy (gene absence and gene loss), may reflect the need to faithfully recognize a multiplicity of pathogen motifs, commensals and a number of self-antigens

Habit Formation and the Persistence of Monetary Shocks

This paper studies the persistent effects of monetary shocks on output. Previous empirical literature documents this persistence, but standard general equilibrium models with sticky prices fail to generate output responses beyond the duration of nominal contracts. This paper constructs and estimates a general equilibrium model with price rigidities, habit formation, and costly capital adjustment. The model is estimated via Maximum Likelihood using US data on output, the real money stock, and the nominal interest rate. Econometric results suggest that habit formation and adjustment costs to capital play an important role in explaining the output effects of monetary policy. In particular, impulse response analysis indicates that the model generates persistent, hump-shaped output responses to monetary shocks.

Estimating the Tobit Model with Serial Correlation: an Operational Approach

Several Authors Have Discussed Recently the Limited Dependent Variable Regression Model with Serial Correlation Between Residuals. the Pseudo-Maximum Likelihood Estimators Obtained by Ignoring Serial Correlation Altogether, Have Been Shown to Be Consistent. We Present Alternative Pseudo-Maximum Likelihood Estimators Which Are Obtained by Ignoring Serial Correlation Only Selectively. Monte Carlo Experiments on a Model with First Order Serial Correlation Suggest That Our Alternative Estimators Have Substantially Lower Mean-Squared Errors in Medium Size and Small Samples, Especially When the Serial Correlation Coefficient Is High. the Same Experiments Also Suggest That the True Level of the Confidence Intervals Established with Our Estimators by Assuming Asymptotic Normality, Is Somewhat Lower Than the Intended Level. Although the Paper Focuses on Models with Only First Order Serial Correlation, the Generalization of the Proposed Approach to Serial Correlation of Higher Order Is Also Discussed Briefly.

Heterotachy and long-branch attraction in phylogenetics

Affiliation: Département de Biochimie, Faculté de médecine, Université de Montréal

Applicabilité de la texture couleur à la différentiation des classes d’occupation du territoire sur des images satellitales multispectrales

La texture est un élément clé pour l’interprétation des images de télédétection à fine résolution spatiale. L’intégration de l’information texturale dans un processus de classification automatisée des images se fait habituellement via des images de texture, souvent créées par le calcul de matrices de co-occurrences (MCO) des niveaux de gris. Une MCO est un histogramme des fréquences d’occurrence des paires de valeurs de pixels présentes dans les fenêtres locales, associées à tous les pixels de l’image utilisée; une paire de pixels étant définie selon un pas et une orientation donnés. Les MCO permettent le calcul de plus d’une dizaine de paramètres décrivant, de diverses manières, la distribution des fréquences, créant ainsi autant d’images texturales distinctes. L’approche de mesure des textures par MCO a été appliquée principalement sur des images de télédétection monochromes (ex. images panchromatiques, images radar monofréquence et monopolarisation). En imagerie multispectrale, une unique bande spectrale, parmi celles disponibles, est habituellement choisie pour générer des images de texture. La question que nous avons posée dans cette recherche concerne justement cette utilisation restreinte de l’information texturale dans le cas des images multispectrales. En fait, l’effet visuel d’une texture est créé, non seulement par l’agencement particulier d’objets/pixels de brillance différente, mais aussi de couleur différente. Plusieurs façons sont proposées dans la littérature pour introduire cette idée de la texture à plusieurs dimensions. Parmi celles-ci, deux en particulier nous ont intéressés dans cette recherche. La première façon fait appel aux MCO calculées bande par bande spectrale et la seconde utilise les MCO généralisées impliquant deux bandes spectrales à la fois. Dans ce dernier cas, le procédé consiste en le calcul des fréquences d’occurrence des paires de valeurs dans deux bandes spectrales différentes. Cela permet, en un seul traitement, la prise en compte dans une large mesure de la « couleur » des éléments de texture. Ces deux approches font partie des techniques dites intégratives. Pour les distinguer, nous les avons appelées dans cet ouvrage respectivement « textures grises » et « textures couleurs ». Notre recherche se présente donc comme une analyse comparative des possibilités offertes par l’application de ces deux types de signatures texturales dans le cas spécifique d’une cartographie automatisée des occupations de sol à partir d’une image multispectrale. Une signature texturale d’un objet ou d’une classe d’objets, par analogie aux signatures spectrales, est constituée d’une série de paramètres de texture mesurés sur une bande spectrale à la fois (textures grises) ou une paire de bandes spectrales à la fois (textures couleurs). Cette recherche visait non seulement à comparer les deux approches intégratives, mais aussi à identifier la composition des signatures texturales des classes d’occupation du sol favorisant leur différentiation : type de paramètres de texture / taille de la fenêtre de calcul / bandes spectrales ou combinaisons de bandes spectrales. Pour ce faire, nous avons choisi un site à l’intérieur du territoire de la Communauté Métropolitaine de Montréal (Longueuil) composé d’une mosaïque d’occupations du sol, caractéristique d’une zone semi urbaine (résidentiel, industriel/commercial, boisés, agriculture, plans d’eau…). Une image du satellite SPOT-5 (4 bandes spectrales) de 10 m de résolution spatiale a été utilisée dans cette recherche. Puisqu’une infinité d’images de texture peuvent être créées en faisant varier les paramètres de calcul des MCO et afin de mieux circonscrire notre problème nous avons décidé, en tenant compte des études publiées dans ce domaine : a) de faire varier la fenêtre de calcul de 3*3 pixels à 21*21 pixels tout en fixant le pas et l’orientation pour former les paires de pixels à (1,1), c'est-à-dire à un pas d’un pixel et une orientation de 135°; b) de limiter les analyses des MCO à huit paramètres de texture (contraste, corrélation, écart-type, énergie, entropie, homogénéité, moyenne, probabilité maximale), qui sont tous calculables par la méthode rapide de Unser, une approximation des matrices de co-occurrences, c) de former les deux signatures texturales par le même nombre d’éléments choisis d’après une analyse de la séparabilité (distance de Bhattacharya) des classes d’occupation du sol; et d) d’analyser les résultats de classification (matrices de confusion, exactitudes, coefficients Kappa) par maximum de vraisemblance pour conclure sur le potentiel des deux approches intégratives; les classes d’occupation du sol à reconnaître étaient : résidentielle basse et haute densité, commerciale/industrielle, agricole, boisés, surfaces gazonnées (incluant les golfs) et plans d’eau. Nos principales conclusions sont les suivantes a) à l’exception de la probabilité maximale, tous les autres paramètres de texture sont utiles dans la formation des signatures texturales; moyenne et écart type sont les plus utiles dans la formation des textures grises tandis que contraste et corrélation, dans le cas des textures couleurs, b) l’exactitude globale de la classification atteint un score acceptable (85%) seulement dans le cas des signatures texturales couleurs; c’est une amélioration importante par rapport aux classifications basées uniquement sur les signatures spectrales des classes d’occupation du sol dont le score est souvent situé aux alentours de 75%; ce score est atteint avec des fenêtres de calcul aux alentours de11*11 à 15*15 pixels; c) Les signatures texturales couleurs offrant des scores supérieurs à ceux obtenus avec les signatures grises de 5% à 10%; et ce avec des petites fenêtres de calcul (5*5, 7*7 et occasionnellement 9*9) d) Pour plusieurs classes d’occupation du sol prises individuellement, l’exactitude dépasse les 90% pour les deux types de signatures texturales; e) une seule classe est mieux séparable du reste par les textures grises, celle de l’agricole; f) les classes créant beaucoup de confusions, ce qui explique en grande partie le score global de la classification de 85%, sont les deux classes du résidentiel (haute et basse densité). En conclusion, nous pouvons dire que l’approche intégrative par textures couleurs d’une image multispectrale de 10 m de résolution spatiale offre un plus grand potentiel pour la cartographie des occupations du sol que l’approche intégrative par textures grises. Pour plusieurs classes d’occupations du sol un gain appréciable en temps de calcul des paramètres de texture peut être obtenu par l’utilisation des petites fenêtres de traitement. Des améliorations importantes sont escomptées pour atteindre des exactitudes de classification de 90% et plus par l’utilisation des fenêtres de calcul de taille variable adaptées à chaque type d’occupation du sol. Une méthode de classification hiérarchique pourrait être alors utilisée afin de séparer les classes recherchées une à la fois par rapport au reste au lieu d’une classification globale où l’intégration des paramètres calculés avec des fenêtres de taille variable conduirait inévitablement à des confusions entre classes.