SVR-GARCH com misturas de kernels gaussianos

Dissertação (mestrado)—Universidade de Brasília, Departamento de Administração, Programa de Pós-graduação em Administração, 2016.

Subject response rates in case-control studies of cancer : time trends, study design determinants, and quality of reporting

Objectifs: Examiner les tendances temporelles, les déterminants en lien avec le design des études et la qualité des taux de réponse rapportés dans des études cas-témoins sur le cancer publiées lors des 30 dernières années. Méthodes: Une revue des études cas-témoins sur le cancer a été menée. Les critères d'inclusion étaient la publication (i) dans l’un de 15 grands périodiques ciblés et (ii) lors de quatre périodes de publication (1984-1986, 1995, 2005 et 2013) couvrant trois décennies. 370 études ont été sélectionnées et examinées. La méthodologie en lien avec le recrutement des sujets et la collecte de données, les caractéristiques de la population, les taux de participation et les raisons de la non-participation ont été extraites de ces études. Des statistiques descriptives ont été utilisées pour résumer la qualité des taux de réponse rapportés (en fonction de la quantité d’information disponible), les tendances temporelles et les déterminants des taux de réponse; des modèles de régression linéaire ont été utilisés pour analyser les tendances temporelles et les déterminants des taux de participation. Résultats: Dans l'ensemble, les qualités des taux de réponse rapportés et des raisons de non-participation étaient très faible, particulièrement chez les témoins. La participation a diminué au cours des 30 dernières années, et cette baisse est plus marquée dans les études menées après 2000. Lorsque l'on compare les taux de réponse dans les études récentes a ceux des études menées au cours de 1971 à 1980, il y a une plus grande baisse chez les témoins sélectionnés en population générale ( -17,04%, IC 95%: -23,17%, -10,91%) que chez les cas (-5,99%, IC 95%: -11,50%, -0,48%). Les déterminants statistiquement significatifs du taux de réponse chez les cas étaient: le type de cancer examiné, la localisation géographique de la population de l'étude, et le mode de collecte des données. Le seul déterminant statistiquement significatif du taux de réponse chez les témoins hospitaliers était leur localisation géographique. Le seul déterminant statistiquement significatif du taux de participation chez les témoins sélectionnés en population générale était le type de répondant (sujet uniquement ou accompagné d’une tierce personne). Conclusion: Le taux de participation dans les études cas-témoins sur le cancer semble avoir diminué au cours des 30 dernières années et cette baisse serait plus marquée dans les études récentes. Afin d'évaluer le niveau réel de non-participation et ses déterminants, ainsi que l'impact de la non-participation sur la validité des études, il est nécessaire que les études publiées utilisent une approche normalisée pour calculer leurs taux de participation et qu’elles rapportent ceux-ci de façon transparente.

Recent advances in explaining hedge fund returns:implicit factors and exposures

We survey articles covering how hedge fund returns are explained, using largely non-linear multifactor models that examine the non-linear pay-offs and exposures of hedge funds. We provide an integrated view of the implicit factor and statistical factor models that are largely able to explain the hedge fund return-generating process. We present their evolution through time by discussing pioneering studies that made a significant contribution to knowledge, and also recent innovative studies that examine hedge fund exposures using advanced econometric methods. This is the first review that analyzes very recent studies that explain a large part of hedge fund variation. We conclude by presenting some gaps for future research.

Subject response rates in case-control studies of cancer : time trends, study design determinants, and quality of reporting

Objectifs: Examiner les tendances temporelles, les déterminants en lien avec le design des études et la qualité des taux de réponse rapportés dans des études cas-témoins sur le cancer publiées lors des 30 dernières années. Méthodes: Une revue des études cas-témoins sur le cancer a été menée. Les critères d'inclusion étaient la publication (i) dans l’un de 15 grands périodiques ciblés et (ii) lors de quatre périodes de publication (1984-1986, 1995, 2005 et 2013) couvrant trois décennies. 370 études ont été sélectionnées et examinées. La méthodologie en lien avec le recrutement des sujets et la collecte de données, les caractéristiques de la population, les taux de participation et les raisons de la non-participation ont été extraites de ces études. Des statistiques descriptives ont été utilisées pour résumer la qualité des taux de réponse rapportés (en fonction de la quantité d’information disponible), les tendances temporelles et les déterminants des taux de réponse; des modèles de régression linéaire ont été utilisés pour analyser les tendances temporelles et les déterminants des taux de participation. Résultats: Dans l'ensemble, les qualités des taux de réponse rapportés et des raisons de non-participation étaient très faible, particulièrement chez les témoins. La participation a diminué au cours des 30 dernières années, et cette baisse est plus marquée dans les études menées après 2000. Lorsque l'on compare les taux de réponse dans les études récentes a ceux des études menées au cours de 1971 à 1980, il y a une plus grande baisse chez les témoins sélectionnés en population générale ( -17,04%, IC 95%: -23,17%, -10,91%) que chez les cas (-5,99%, IC 95%: -11,50%, -0,48%). Les déterminants statistiquement significatifs du taux de réponse chez les cas étaient: le type de cancer examiné, la localisation géographique de la population de l'étude, et le mode de collecte des données. Le seul déterminant statistiquement significatif du taux de réponse chez les témoins hospitaliers était leur localisation géographique. Le seul déterminant statistiquement significatif du taux de participation chez les témoins sélectionnés en population générale était le type de répondant (sujet uniquement ou accompagné d’une tierce personne). Conclusion: Le taux de participation dans les études cas-témoins sur le cancer semble avoir diminué au cours des 30 dernières années et cette baisse serait plus marquée dans les études récentes. Afin d'évaluer le niveau réel de non-participation et ses déterminants, ainsi que l'impact de la non-participation sur la validité des études, il est nécessaire que les études publiées utilisent une approche normalisée pour calculer leurs taux de participation et qu’elles rapportent ceux-ci de façon transparente.

Young people's well-being and the economic crisis: How does parental unemployment and family wealth affect the downturn experience?

Background: Portugal is among the European countriesmost severely hit by the economic recession and the fifth with the highest unemployment rate. Given that adolescents' development is highly influenced by their living contexts, monitoring the repercussions of the economic recession is essential for the evaluation and improvement of their current and future public health. Objective: To investigate youth perceived repercussions of the economic recession, its association with life satisfaction, as well as to assess differences across parental employment status and family perceived wealth. Methods: Data were drawn from the Portuguese 2014 Health Behaviour in School-aged children survey, aWHO collaborative cross-national study, with a nationally representative sample of 2748 students (Mage = 14.7 years ± 1.2; 48% boys). Descriptive statistics and linear regression models were performed. Results: Levels of life satisfaction are lower when young people perceive that the economic recession generated negative lifestyle changes. Having unemployed parents was found to be significantly associated with perceiving such repercussions and family wealth to decrease the perception of repercussions of the recession. Conclusions: Findings enhance our understanding of how Portuguese youth are being affected by the socioeconomic conditions surrounding them. Such information contributes to improve future research and also allow some considerations about the policies aimed at protecting young people'swellbeing during a period of high unemployment and socioeconomic downturn.

Dinâmica fisiológica da variabilidade cardíaca: uma abordagem estatística na síncope vasovagal

Introdução: A perda transitória da consciência e tónus postural seguido de rápida recuperação é definida como síncope. Tem sido dada atenção a uma síncope de origem central com descida da pressão sistémica conhecida por síncope vasovagal (SVV). Objetivos: A análise da variabilidade da frequência cardíaca (HRV) é uma das principais estratégias para estudar a SVV através de protocolos padrão (por exemplo tilt test). O principal objetivo deste trabalho é compreender a importância relativa de diversas variáveis, tais como pressão arterial diastólica e sistólica, (dBP) e (sBP), volume sistólico (SV) e resistência periférica total (TPR) na HRV. Métodos: Foram usados modelos estatísticos mistos para modelar o comportamento das variáveis acima descritas na HRV. Analisaram-se mais de mil e quinhentas observações de quatro pacientes com SVV, previamente testados com análise espectral clássica para a fase basal (LF/HF=3.01) e fases de tilt (LF/HF=0.64), indicando uma predominância vagal no período tilt. Resultados: O modelo 1 revelou o papel importante da dBP e uma baixa influência de SV, na fase de tilt, relativos à HRV. No modelo 2 a TPR revelou uma baixa influência na HRV na fase de tilt entre os pacientes. Conclusões: Verificou-se que a HRV é influenciada por um conjunto de variáveis fisiológicas, cuja contribuição individual pode ser usada para compreender as flutuações cardíacas. O uso de modelos estatísticos salientou a importância de estudar o papel da dBP e SV na SVV.

A Microdata Analysis Approach to Transport Infrastructure Maintenance

Maintenance of transport infrastructure assets is widely advocated as the key in minimizing current and future costs of the transportation network. While effective maintenance decisions are often a result of engineering skills and practical knowledge, efficient decisions must also account for the net result over an asset's life-cycle. One essential aspect in the long term perspective of transport infrastructure maintenance is to proactively estimate maintenance needs. In dealing with immediate maintenance actions, support tools that can prioritize potential maintenance candidates are important to obtain an efficient maintenance strategy. This dissertation consists of five individual research papers presenting a microdata analysis approach to transport infrastructure maintenance. Microdata analysis is a multidisciplinary field in which large quantities of data is collected, analyzed, and interpreted to improve decision-making. Increased access to transport infrastructure data enables a deeper understanding of causal effects and a possibility to make predictions of future outcomes. The microdata analysis approach covers the complete process from data collection to actual decisions and is therefore well suited for the task of improving efficiency in transport infrastructure maintenance. Statistical modeling was the selected analysis method in this dissertation and provided solutions to the different problems presented in each of the five papers. In Paper I, a time-to-event model was used to estimate remaining road pavement lifetimes in Sweden. In Paper II, an extension of the model in Paper I assessed the impact of latent variables on road lifetimes; displaying the sections in a road network that are weaker due to e.g. subsoil conditions or undetected heavy traffic. The study in Paper III incorporated a probabilistic parametric distribution as a representation of road lifetimes into an equation for the marginal cost of road wear. Differentiated road wear marginal costs for heavy and light vehicles are an important information basis for decisions regarding vehicle miles traveled (VMT) taxation policies. In Paper IV, a distribution based clustering method was used to distinguish between road segments that are deteriorating and road segments that have a stationary road condition. Within railway networks, temporary speed restrictions are often imposed because of maintenance and must be addressed in order to keep punctuality. The study in Paper V evaluated the empirical effect on running time of speed restrictions on a Norwegian railway line using a generalized linear mixed model.

Variation in myogenic differentiation 1 mRNA abundance is associated with beef tenderness in Nelore cattle.

The myogenic differentiation 1 gene (MYOD1) has a key role in skeletal muscle differentiation and composition through its regulation of the expression of several muscle-specific genes. We first used a general linear mixed model approach to evaluate the association of MYOD1 expression levels on individual beef tenderness phenotypes. MYOD1 mRNA levels measured by quantitative polymerase chain reactions in 136 Nelore steers were significantly associated (P ? 0.01) with Warner?Bratzler shear force, measured on the longissimus dorsi muscle after 7 and 14 days of beef aging. Transcript abundance for the muscle regulatory gene MYOD1 was lower in animals with more tender beef. We also performed a coexpression network analysis using whole transcriptome sequence data generated from 30 samples of longissimus muscle tissue to identify genes that are potentially regulated by MYOD1. The effect of MYOD1 gene expression on beef tenderness may emerge from its function as an activator of muscle-specific gene transcription such as for the serum response factor (C-fos serum response element-binding transcription factor) gene (SRF), which determines muscle tissue development, composition, growth and maturation.

Improved testing inference in mixed linear models

Mixed linear models are commonly used in repeated measures studies. They account for the dependence amongst observations obtained from the same experimental unit. Often, the number of observations is small, and it is thus important to use inference strategies that incorporate small sample corrections. In this paper, we develop modified versions of the likelihood ratio test for fixed effects inference in mixed linear models. In particular, we derive a Bartlett correction to such a test, and also to a test obtained from a modified profile likelihood function. Our results generalize those in [Zucker, D.M., Lieberman, O., Manor, O., 2000. Improved small sample inference in the mixed linear model: Bartlett correction and adjusted likelihood. Journal of the Royal Statistical Society B, 62,827-838] by allowing the parameter of interest to be vector-valued. Additionally, our Bartlett corrections allow for random effects nonlinear covariance matrix structure. We report simulation results which show that the proposed tests display superior finite sample behavior relative to the standard likelihood ratio test. An application is also presented and discussed. (C) 2008 Elsevier B.V. All rights reserved.

Bilevel approach for optimal location and contract pricing of distributed generation in radial distribution systems using mixed-integer linear programming

In this study, a novel approach for the optimal location and contract pricing of distributed generation (DG) is presented. Such an approach is designed for a market environment in which the distribution company (DisCo) can buy energy either from the wholesale energy market or from the DG units within its network. The location and contract pricing of DG is determined by the interaction between the DisCo and the owner of the distributed generators. The DisCo intends to minimise the payments incurred in meeting the expected demand, whereas the owner of the DG intends to maximise the profits obtained from the energy sold to the DisCo. This two-agent relationship is modelled in a bilevel scheme. The upper-level optimisation is for determining the allocation and contract prices of the DG units, whereas the lower-level optimisation is for modelling the reaction of the DisCo. The bilevel programming problem is turned into an equivalent single-level mixed-integer linear optimisation problem using duality properties, which is then solved using commercially available software. Results show the robustness and efficiency of the proposed model compared with other existing models. As regards to contract pricing, the proposed approach allowed to find better solutions than those reported in previous works. © The Institution of Engineering and Technology 2013.

Relative entropy rate based design for linear hybrid system models

Hybrid system representations have been applied to many challenging modeling situations. In these hybrid system representations, a mixture of continuous and discrete states is used to capture the dominating behavioural features of a nonlinear, possible uncertain, model under approximation. Unfortunately, the problem of how to best design a suitable hybrid system model has not yet been fully addressed. This paper proposes a new joint state measurement relative entropy rate based approach for this design purpose. Design examples and simulation studies are presented which highlight the benefits of our proposed design approaches.

Linear models for endocytic transformations from live cell imaging

Endocytosis is the process by which cells internalise molecules including nutrient proteins from the extracellular media. In one form, macropinocytosis, the membrane at the cell surface ruffles and folds over to give rise to an internalised vesicle. Negatively charged phospholipids within the membrane called phosphoinositides then undergo a series of transformations that are critical for the correct trafficking of the vesicle within the cell, and which are often pirated by pathogens such as Salmonella. Advanced fluorescent video microscopy imaging now allows the detailed observation and quantification of these events in live cells over time. Here we use these observations as a basis for building differential equation models of the transformations. An initial investigation of these interactions was modelled with reaction rates proportional to the sum of the concentrations of the individual constituents. A first order linear system for the concentrations results. The structure of the system enables analytical expressions to be obtained and the problem becomes one of determining the reaction rates which generate the observed data plots. We present results with reaction rates which capture the general behaviour of the reactions so that we now have a complete mathematical model of phosphoinositide transformations that fits the experimental observations. Some excellent fits are obtained with modulated exponential functions; however, these are not solutions of the linear system. The question arises as to how the model may be modified to obtain a system whose solution provides a more accurate fit.

PySSM : a Python module for Bayesian inference of linear Gaussian state space models

PySSM is a Python package that has been developed for the analysis of time series using linear Gaussian state space models (SSM). PySSM is easy to use; models can be set up quickly and efficiently and a variety of different settings are available to the user. It also takes advantage of scientific libraries Numpy and Scipy and other high level features of the Python language. PySSM is also used as a platform for interfacing between optimised and parallelised Fortran routines. These Fortran routines heavily utilise Basic Linear Algebra (BLAS) and Linear Algebra Package (LAPACK) functions for maximum performance. PySSM contains classes for filtering, classical smoothing as well as simulation smoothing.