Archive of past events of the site Institute of Statistics, Biostatistics and Actuarial Sciences
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Applied Statistics Workshop by Anna Malinovskaya16 May16:00 - "Beyond Tables: Unlocking the World of Spatial Data" Anna Malinovskaya (Nala Earth)Beyond Tables: Unlocking the World of Spatial DataAbstract: This presentation explores how geospatial data is different beyond traditional data structures.En savoir plusApplied Statistics Workshop by Anna Malinovskaya16 May16:00 - "Beyond Tables: Unlocking the World of Spatial Data" Anna Malinovskaya (Nala Earth)Beyond Tables: Unlocking the World of Spatial DataAbstract: This presentation explores how geospatial data is different beyond traditional data structures.
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Applied Statistics Workshop by Thomas Delclite16 May14:30 - "Méthodologie des enquêtes en statistique publique : de l’échantillonnage à l’estimation de la variance " Thomas Delclite(StatBel)Méthodologie des enquêtes en statistique publique : de l’échantillonnage à l’estimation de la variance Abstract: Ce séminaire présente les principales étapes méthodologiques mises en œuvre dans la production d’enquêtes statistiques à StatbelEn savoir plusApplied Statistics Workshop by Thomas Delclite16 May14:30 - "Méthodologie des enquêtes en statistique publique : de l’échantillonnage à l’estimation de la variance " Thomas Delclite(StatBel)Méthodologie des enquêtes en statistique publique : de l’échantillonnage à l’estimation de la variance Abstract: Ce séminaire présente les principales étapes méthodologiques mises en œuvre dans la production d’enquêtes statistiques à Statbel
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Applied Statistics Workshop by Jens Robben18 Apr14:30 - 17:00 : "The short-term association between environmental variables and mortality: evidence from Europe" - Jens Robben Jens Robben (University of Amsterdam)The short-term association between environmental variables and mortality: evidence from EuropeAbstract: In this workshop, we study the short-term association between environmental factors, i.e., weather and air polEn savoir plusApplied Statistics Workshop by Jens Robben18 Apr14:30 - 17:00 : "The short-term association between environmental variables and mortality: evidence from Europe" - Jens Robben Jens Robben (University of Amsterdam)The short-term association between environmental variables and mortality: evidence from EuropeAbstract: In this workshop, we study the short-term association between environmental factors, i.e., weather and air pol
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Statistics Seminar by Jeroen Rombouts18 Apr11:00 - "Modeling Higher Moments and Risk Premia for S&P 500 Returns" Jeroen Rombouts (ESSEC Business School) Modeling Higher Moments and Risk Premia for S&P 500 ReturnsAbstract: We study the impact of additional option pricing model factors on the level, term structure and conditional properties of index return moments and their risk premia.En savoir plusStatistics Seminar by Jeroen Rombouts18 Apr11:00 - "Modeling Higher Moments and Risk Premia for S&P 500 Returns" Jeroen Rombouts (ESSEC Business School) Modeling Higher Moments and Risk Premia for S&P 500 ReturnsAbstract: We study the impact of additional option pricing model factors on the level, term structure and conditional properties of index return moments and their risk premia.
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Statistics Seminar by Alexander Munteanu11 Apr14:30 - "\ell_p Sensitivity Sampling: Optimal bounds and an Application to Poisson pth-Root-Link Models" Alexander Munteanu \ell_p Sensitivity Sampling: Optimal bounds and an Application to Poisson pth-Root-Link Models Abstract: Sensitivity sampling is a general purpose technique for importance subsampling that is very popular for the construction of \ell_p subspace embedEn savoir plusStatistics Seminar by Alexander Munteanu11 Apr14:30 - "\ell_p Sensitivity Sampling: Optimal bounds and an Application to Poisson pth-Root-Link Models" Alexander Munteanu \ell_p Sensitivity Sampling: Optimal bounds and an Application to Poisson pth-Root-Link Models Abstract: Sensitivity sampling is a general purpose technique for importance subsampling that is very popular for the construction of \ell_p subspace embed
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Applied Statistics Workshop by Marie-Pier Côté21 Mar16:00 - "Un modèle hiérarchique flexible pour les réclamations d'assurance combinant gradient boosting et copules" Marie-Pier Côté (l’université Laval) Un modèle hiérarchique flexible pour les réclamations d'assurance combinant gradient boosting et copules Résumé : Nous proposons un modèle hiérarchique pour les réclamations en assurance de dommage qui affine les méthodesEn savoir plusApplied Statistics Workshop by Marie-Pier Côté21 Mar16:00 - "Un modèle hiérarchique flexible pour les réclamations d'assurance combinant gradient boosting et copules" Marie-Pier Côté (l’université Laval) Un modèle hiérarchique flexible pour les réclamations d'assurance combinant gradient boosting et copules Résumé : Nous proposons un modèle hiérarchique pour les réclamations en assurance de dommage qui affine les méthodes
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Applied Statistics Workshop by Joelle Desterbecq21 Mar14:30 - "Open Science et gestion des données de la recherche : objectifs, principes et ressources" Joelle Desterbecq (UCLouvain) Open Science et gestion des données de la recherche : objectifs, principes et ressourcesRésumé: Vous souhaitez en savoir plus sur l’Open Science ? Vous démarrez un nouveau projet et vous devez établir un plan de gestion des données ?En savoir plusApplied Statistics Workshop by Joelle Desterbecq21 Mar14:30 - "Open Science et gestion des données de la recherche : objectifs, principes et ressources" Joelle Desterbecq (UCLouvain) Open Science et gestion des données de la recherche : objectifs, principes et ressourcesRésumé: Vous souhaitez en savoir plus sur l’Open Science ? Vous démarrez un nouveau projet et vous devez établir un plan de gestion des données ?
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Evènement en l’honneur de Jean-Marie Rolin14 Mar14h - Accueil / introduction, Léopold Simar, Professeur émérite à et fondateur de l’Institut de statistique (STAT, devenu ISBA-LSBA-SMCS), UCLouvain et Jean-Pierre Florens, Professeur émérite, TSE, Toulouse School of Economics14h05 - 14h45 – Anna Simoni, ENSAE ParisTitle : Panel data models with randomly generated groups: Bayesian inference and density forecasts14h45 - 15h25 – Philippe Lambert, UCEn savoir plusEvènement en l’honneur de Jean-Marie Rolin14 Mar14h - Accueil / introduction, Léopold Simar, Professeur émérite à et fondateur de l’Institut de statistique (STAT, devenu ISBA-LSBA-SMCS), UCLouvain et Jean-Pierre Florens, Professeur émérite, TSE, Toulouse School of Economics14h05 - 14h45 – Anna Simoni, ENSAE ParisTitle : Panel data models with randomly generated groups: Bayesian inference and density forecasts14h45 - 15h25 – Philippe Lambert, UC
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Statistics Seminar by Joshua Loftus07 Mar14:30 - "Causal interpretability for human-centered data science" - Joshua Loftus Joshua Loftus (London School of Economics (LSE)) Causal interpretability for human-centered data scienceAbstract: Tools for interpretable machine learning or explainable artificial intelligence can be used to audit algorithms for fairness or other desired properties.En savoir plusStatistics Seminar by Joshua Loftus07 Mar14:30 - "Causal interpretability for human-centered data science" - Joshua Loftus Joshua Loftus (London School of Economics (LSE)) Causal interpretability for human-centered data scienceAbstract: Tools for interpretable machine learning or explainable artificial intelligence can be used to audit algorithms for fairness or other desired properties.
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Statistics Seminar by Fabian Mies28 Feb14:30 - "Projection inference for high-dimensional covariance matrices" - Fabian Mies (TU Delft) Projection inference for high-dimensional covariance matrices Abstract: Analyzing large samples of high-dimensional data under dependence is a challenging statistical problem as long time series may have change points, most importantly in the mean and the marginal covariances,En savoir plusStatistics Seminar by Fabian Mies28 Feb14:30 - "Projection inference for high-dimensional covariance matrices" - Fabian Mies (TU Delft) Projection inference for high-dimensional covariance matrices Abstract: Analyzing large samples of high-dimensional data under dependence is a challenging statistical problem as long time series may have change points, most importantly in the mean and the marginal covariances,