Publications des institutions partenaires
Capitalizing upon the attractive and addictive properties of massively multiplayer online role-playing games to promote wellbeing
Institution partenaire
English / 01/01/2016
A predictive based regression algorithm for gene network selection
Gene selection has become a common task in most gene expression studies. The objective of such research is often to identify the smallest possible set of genes that can still achieve good predictive performance. To do so, many of the recently proposed classification methods require some form of dimension-reduction of the problem which finally provide a single model as an output and,...
Institution partenaire
English / 01/01/2016
Time-frequency Granger causality with application to nonstationary brain signals
This PhD thesis concerns the modelling of time-varying causal relationships between two signals, with a focus on signals measuring neural activities. The ability to compute a dynamic and frequency-specific causality statistic in this context is essential and Granger causality provides a natural statistical tool. In Chapter 1 we propose a review of the existing methods allowing one to...
Institution partenaire
English / 01/01/2015
Robust Inference for Time Series Models: a Wavelet-Based Framework
We present a new framework for the robust estimation of time series models which is fairly general and, for example, covers models going from ARMA to state-space models. This approach provides estimators which are (i) consistent and asymptotically normally distributed, (ii) applicable to a broad spectrum of time series models, (iii) straightforward to implement and (iv)...
Institution partenaire
English / 01/01/2015
Simulation based bias correction methods for complex problems
Nowadays, the increase in data size and model complexity has led to increasingly difficult estimation problems. The numerical aspects of the estimation procedure can indeed be very challenging. To solve these estimation problems, approximate methods such as pseudo-likelihood functions or approximated estimating equations can be used as these methods are typically easier to implement...
Institution partenaire
English / 01/01/2015
Implicitly assessed attitudes toward body shape and food: the moderating roles of dietary restraint and disinhibition
Background: Attitudes toward body shape and food play a role in the development and maintenance of dysfunctional eating behaviors. Nevertheless, they are rarely investigated together. Therefore, this study aimed to explore the interrelationships between implicitly assessed attitudes toward body shape and food and to investigate the moderating effect on these associations of...
Institution partenaire
Français / 01/01/2015
Prevalence and characteristics of addictive behaviors in a community sample: A latent class analysis
While addictions to substances such as alcohol, tobacco, and other drugs have been extensively investigated, interest has been growing in potential non-substance-related addictive behaviors (e.g., excessive gambling, buying or playing video games). In the current study, we sought to determine the prevalence and characteristics of a wide range of addictive behaviors in a general...
Institution partenaire
English / 01/01/2015
Estimating the number of garment factories in Bangladesh
Institution partenaire
English / 01/01/2015
Influence functions for penalized M-estimators
Institution partenaire
English / 01/01/2014
Robust and consistent variable selection for generalized linear and additive models
Institution partenaire
English / 01/01/2014
TError: towards a better quantification of the uncertainty propagated during the characterization of tephra deposits
Institution partenaire
English / 01/01/2014
Semiparametrically Efficient R-Estimation for Dynamic Location-Scale Models
We define rank-based estimators (R-estimators) for semiparametric time series models in whichthe conditional location and scale depend on a Euclidean parameter, while the innovation density isan infinite-dimensional nuisance. Applications include linear and nonlinear models, featuring eitherhomo- or heteroskedasticity (e.g. AR-ARCH and discretely observed diffusions with jumps). We...
Institution partenaire
English / 01/01/2014
Robustness in sample selection models
The problem of non-random sample selectivity often occurs in practice in many different fields. In presence of sample selection, the data appears in the sample according to some selection rule. In these cases, the standard tools designed for complete samples, e.g. ordinary least squares, produce biased results, and hence, methods correcting this bias are needed. In his seminal work,...
Institution partenaire
English / 01/01/2013
Two essays in statistics: a prediction divergence criterion for model selection & wavelet variance based estimation of latent time series models
This thesis is divided in two parts. First, it presents a new criterion for model selection which is shown to be particularly well suited in "sparse" settings which we believe to be common in many research fields. Our selection procedure is developed for linear regression models, smoothing splines, autoregressive and mixed linear models. These developments are then applied...
Institution partenaire
English / 01/01/2013
Robust VIF Regression with Application to Variable Selection in Large Datasets
The sophisticated and automated means of data collection used by an increasing number of institutions and companies leads to extremely large datasets. Subset selection in regression is essential when a huge number of covariates can potentially explain a response variable of interest. The recent statistical literature has seen an emergence of new selection methods that provide some...
Institution partenaire
English / 01/01/2013
Consumer Behavior Analysis for Luxury Goods - A Technical Note for Empirical Studies
Institution partenaire
English / 01/01/2013
Limits of the Allan Variance and Optimal Tuning of Wavelet Variance based Estimators
This article first demonstrates the inconsistency of the estimator based on the standard Allan Variance (AV) for composite stochastic processes. This result motivates the use of a recently developed estimator, called the Generalized Method of Wavelet Moments (GMWM) estimator. This estimator was previously shown to be consistent and asymptotically normally distributed under the...
Institution partenaire
English / 01/01/2013
N-acetylcysteine does not prevent contrast nephropathy in patients with renal impairment undergoing emergency CT: a randomized study
BACKGROUND: Patients admitted to the emergency room with renal impairment and undergoing a contrast computed tomography (CT) are at high risk of developing contrast nephropathy as emergency precludes sufficient hydration prior to contrast use. The value of an ultra-high dose of intravenous N-acetylcysteine in this setting is unknown. METHODS: From 2008 to 2010, we randomized 120...
Institution partenaire
English / 01/01/2013
An Algorithm for Automatic Inertial Sensors Calibration : Proceedings of the ION GNSS 2013
We present an algorithm for determining the nature of stochastic processes together with its parameters based on the analysis of time series of inertial errors. The algorithm is suitable mainly (but not only) for situations when several stochastic processes are superposed. In such cases, classical approaches based on the analysis of Allan variance or PSD are likely to fail due to the...
Institution partenaire
English / 01/01/2013
Robust Estimation of Bivariate Copulas
Copula functions are very convenient for modelling multivariate observations. Popular es- timation methods are the two-stage maximum likelihood and an alternative semi-parametric with empirical cumulative distribution functions (cdf) for the margins. Unfortunately, they can be hastily biased whenever relatively small model deviations occur at the marginal (empirical or parametric)...
Institution partenaire
English / 01/01/2013
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