Publications des institutions partenaires

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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...

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Université de Genève

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English / 01/01/2018

Parametric inference for index functionals

In this paper, we study the finite sample accuracy of confidence intervals for index functional built via parametric bootstrap, in the case of inequality indices. To estimate the parameters of the assumed parametric data generating distribution, we propose a Generalized Method of Moment estimator that targets the quantity of interest, namely the considered inequality index. Its...

Institution partenaire

Université de Genève

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Français / 01/01/2018

Statistique inférentielle

Institution partenaire

Université de Genève

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Français / 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

Université de Genève

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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

Université de Genève

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English / 01/01/2018

Assessment of dysfunctional cognitions in binge-eating disorder: factor structure and validity of the mizes anorectic cognitions questionnaire-revised (mac-r)

Dysfunctional cognitions regarding weight and shape and their implications for self-esteem are considered core features of anorexia nervosa and bulimia nervosa. However, they have also been associated with the severity of binge eating disorder (BED). Therefore, they should be screened with appropriate instruments to tailor treatment to individual patient needs. The Mizes Anorectic...

Institution partenaire

Université de Genève

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Français / 01/01/2017

Simulation based bias correction methods for complex models

Along the ever increasing data size and model complexity, an important challenge frequently encountered in constructing new estimators or in implementing a classical one such as the maximum likelihood estimator, is the computational aspect of the estimation procedure. To carry out estimation, approximate methods such as pseudo-likelihood functions or approximated estimating equations...

Institution partenaire

Université de Genève

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Français / 01/01/2017

Discussion of “the power of monitoring: how to make the most of a contaminated multivariate sample” by andrea cerioli, marco riani, anthony c. atkinson and aldo corbellini

This paper discusses the contribution of Cerioli et al. (Stat Methods Appl, 2018), where robust monitoring based on high breakdown point estimators is proposed for multivariate data. The results follow years of development in robust diagnostic techniques. We discuss the issues of extending data monitoring to other models with complex structure, e.g. factor analysis, mixed linear...

Institution partenaire

Université de Genève

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Français / 01/01/2017

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

Université de Genève

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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

Université de Genève

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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

Université de Genève

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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

Université de Genève

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English / 01/01/2017

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

Université de Genève

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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

Université de Genève

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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

Université de Genève

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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

Université de Genève

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English / 01/01/2016

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