Publications des institutions partenaires
A computationally efficient framework for automatic inertial sensor calibration
The calibration of (low-cost) inertial sensors has become increasingly important over the past years since their use has grown exponentially in many applications going from unmanned aerial vehicle navigation to 3D-animation. However, this calibration procedure is often quite problematic since the signals issued from these sensors have a complex spectral structure and the methods…
Institution partenaire
English / 01/01/2018
Effects of substance use disorder on treatment process and outcome in a ten-session psychiatric treatment for borderline personality disorder
Institution partenaire
English / 01/01/2018
Prediction Divergence Criterion for Model Selection in the Logistic Regression
In this Master Thesis, we have analytically derived and numerically implemented three estimators of the Prediction Divergence Criterion (Avella-Medina et al., working paper) for Model Selection within the logistic regression framework. After the validation of these estimators by means of simulations, we have performed Model Selection both when the order of the variables was known in…
Institution partenaire
English / 01/01/2018
Validity and accuracy of posterior distributions in Bayesian statistics
In this thesis I investigate the validity and the accuracy properties of the posterior quantiles in Bayesian statistics when replacing the parametric likelihood with the Cressie-Read empirical likelihoods based on a set of unbiased M-estimating equations. At first order I study the validity of the empirical posterior distribution derived from the pseudo-likelihood constructed with…
Institution partenaire
English / 01/01/2018
The impact of CSR reporting quality on analyst forecast accuracy
We investigate the impact of the quality of corporate social responsibility (CSR) reports on sell-side analyst forecast accuracy. The sample comprises 506 large companies that were selected according to the CSR-Sustainability Monitor, which was used to measure the quality of CSR reports issued in 2012 by the members listed in Fortune 500 US and the Global Index. Forecast error is…
Institution partenaire
English / 08/08/2017
Firm-value effects of CSR disclosure and CSR performance
We examine in this paper the effects of corporate social responsibility (CSR) disclosure and CSR performance on firm value for S&P 500 firms from 2011 to 2014. We find that CSR disclosure is positively associated with firm value and that the effect of CSR disclosure on firm value is larger than the effect of CSR performance. On average, the overall firm value increase for one…
Institution partenaire
English / 30/06/2017
Valuation of the flexibility of power-to-gas facilities
Power-to-gas (P2G) is a technology that converts electrical power to gas fuels like methane for storage in the natural gas grid. Due to the low efficiency, the production of synthetic methane is only profitable if electricity is sufficiently cheap. However, P2G facilities are flexible consumers and can benefit from short-term price fluctuations on the electricity spot market. We use…
Institution partenaire
English / 01/06/2017
Bootstrap estimation of uncertainty in prediction for generalized linear mixed models
In the framework of Mixed Models, it is often of interest to provide an es- timate of the uncertainty in predictions for the random effects, customarily defined by the Mean Squared Error of Prediction (MSEP). To address this computation in the Generalized Linear Mixed Model (GLMM) context, a non-parametric Bootstrap algorithm is proposed. First, a newly developed Bootstrap scheme…
Institution partenaire
English / 01/01/2017
A random-effects hurdle model for predicting bycatch of endangered marine species
Understanding and reducing the incidence of accidental bycatch, particularly for vulnerable species such as sharks, is a major challenge for contemporary fisheries management worldwide. Bycatch data, most often collected by at-sea observers during fishing trips, are clustered by trip and/or vessel and typically involve a large number of zero counts and very few positive counts.…
Institution partenaire
English / 01/01/2017
Established risk factors for addiction fail to discriminate between healthy gamers and gamers endorsing DSM-5 Internet gaming disorder
Background and aims The DSM-5 includes criteria for diagnosing Internet gaming disorder (IGD) that are adapted from substance abuse and widely used in research and clinical contexts, although evidence supporting their validity remains scarce. This study compared online gamers who do or do not endorse IGD criteria regarding self-control-related abilities (impulsivity, inhibitory…
Institution partenaire
English / 01/01/2017
On the Inference of Random Effects in Generalized Linear Mixed Models
In the first chapter, the problem of Bootstrap inference for the parameters of a GLMM is addressed. We formulate a bootstrapping strategy consisting on the random weighting of the contributions to the Joint Likelihood of Outcomes and Random Effects. Using the Laplace Approximation method for integrals on this function, yields a Random Weighted Log-Likelihood that produces the desired…
Institution partenaire
English / 01/01/2017
Prediction of extreme price occurrences in the German day-ahead electricity market
Institution partenaire
English / 01/07/2016
Estimation and application of fully parametric multifactor quantile regression with dynamic coefficients
This paper develops and applies a novel estimation procedure for quantile regressions with time-varying coefficients based on a fully parametric, multifactor specification. The algorithm recursively filters the multifactor dynamic coefficients with a Kalman filter and parameters are estimated by maximum likelihood. The likelihood function is built on the Skewed-Laplace assumption. In…
Institution partenaire
English / 15/06/2016
A fully parametric approach for solving quantile regressions with time-varying coefficients
This paper develops and applies a novel estimation procedure for quantile regressions with time-varying coefficients based on a fully parametric, multifactor specification. The algorithm recursively filters the multifactor dynamic coefficients with a Kalman filter and parameters are estimated by maximum likelihood. The likelihood function is built on the Skewed-Laplace assumption. In…
Institution partenaire
English / 04/06/2016
Structural model for electricity forward prices
Structural models for forward electricity prices are of great relevance nowadays, given the major structural changes in the market due to the increase of renewable energy in the production mix. In this study, we aim at understanding the dynamics of the risk premium (the drift in the dynamics) and the noise (non-Gaussian, stochastic volatility) in futures prices for electricity. We…
Institution partenaire
English / 28/04/2016
Confidence sets for model selection
At first glance the goals of model selection might seem clear. Out of a set of possible models, we want to select the ”best” or a subset of ”best” models. This notion of ”best” however is not well defined, since it obviously depends on the initial goals of the selection. In order to study the uncertainty in model selection, we introduce a new definition of a model, where the models…
Institution partenaire
English / 01/01/2016
Robust inference for random fields and latent models
This thesis delivers a new framework for the robust parametric estimation of random fields and latent models through the use of the wavelet variance. By proposing a new M-estimation approach for the latter quantity and delivering results on the identifiability of a wide class of latent models, the thesis finally delivers a computationally efficient and statistically sound method to…
Institution partenaire
English / 01/01/2016
Measures of model adequacy and model selection in mixed-effects models
This thesis contributes to the development of measures of model selection and model adequacy for mixed-effects models. In the context of linear mixed-effects models, we review and compare in a simulation study a large set of measures proposed to evaluate model adequacy or/and to perform model selection. In the more general context of generalized linear mixed-effects models, we…
Institution partenaire
English / 01/01/2016
Robust penalized M-estimators for generalized linear and additive models
Generalized linear models (GLM) and generalized additive models (GAM) are popular statistical methods for modelling continuous and discrete data both parametrically and nonparametrically. In this general framework, we consider the problem of variable selection by studying a wide class of penalized M-estimators that are particularly well suited for high dimensional scenarios where the…
Institution partenaire
English / 01/01/2016
Capitalizing upon the attractive and addictive properties of massively multiplayer online role-playing games to promote wellbeing
Institution partenaire
English / 01/01/2016
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