Search results for "Statistique"

Génèse et évolution des compétences des élèves à la fin de l'école maternelle : éléments d'analyse à partir de données de panel et d'une expérimentat…

2012

We propose to study in this thesis, a key issue and relatively little discussed in the French research in educational sciences, it concerns the genesis of pupil learning and their evolution during the tuition. We mobilize a longitudinal data (Panel 1997) and the results of a musical experimentation in kindergarten to answer to these questions: How are structured the first acquisitions of pupils and how is it linked to the school context and socio-economic variables? How the cognitive abilities of students affect their academic performance? Are specific activities can improve academic skills through an increase in cognitive abilities? Implicative analysis conducted on panel data has revealed…

Segmentation automatique et analyse de forme d'hippocampes humains dans l'étude de la maladie d'Alzheimer

2011

The aim of this thesis is to investigate the shape change in hippocampus due to the atrophy in Alzheimer’s disease (AD). To this end, specific algorithms and methodologies were developed to segment the hippocampus from structural magnetic resonance (MR) images and model variations in its shape. We use a multi-atlas based segmentation propagation approach for the segmentation of hippocampus which has been shown to obtain accurate parcellation of brain structures. We developed a supervised method to build a population specific atlas database, by propagating the parcellations from a smaller generic atlas database. Well segmented images are inspected and added to the set of atlases, such that t…

From optimization to algorithmic differentiation: a graph detour

2021

This manuscript highlights the work of the author since he was nominated as "Chargé de Recherche" (research scientist) at Centre national de la recherche scientifique (CNRS) in 2015. In particular, the author shows a thematic and chronological evolution of his research interests:- The first part, following his post-doctoral work, is concerned with the development of new algorithms for non-smooth optimization.- The second part is the heart of his research in 2020. It is focused on the analysis of machine learning methods for graph (signal) processing.- Finally, the third and last part, oriented towards the future, is concerned with (automatic or not) differentiation of algorithms for learnin…

Forecasting Methodology for Qualification and Training Needs in France

1999

The present publication is the first outcome of the European project "Labouratory" which aims at elaborating forecasting methodology applicable in the transition countries of Central Europe. This paper takes stock of the labour market data and methods used to forecast education and training needs in France : at the national level, only one institute (BIPE) suggests a model for calculating recruitement needs according to professional categories ; on the sectoral level, roughly twenty professional branches carried out forecasting study contracts ; OREF Bourgogne works at the regional level with available data national statistics in composition with qualitative school and company surveys, broa…

Rapport annuel 2006-2007 de l'Observatoire national de la démographie des professions de santé.

2008

Ce troisième rapport de l'Observatoire national de la démographie des professions de santé comporte une synthèse générale assortie de préconisations et de quatre tomes thématiques : la médecine générale (tome 1), les internes en médecine (tome 2), la profession de chirurgien dentiste et les métiers de la périnatalité (tome 3), les métiers de la cancérologie (tome 4).

Optimal signed-rank tests based on hyperplanes

2005

Abstract For analysing k -variate data sets, Randles (J. Amer. Statist. Assoc. 84 (1989) 1045) considered hyperplanes going through k - 1 data points and the origin. He then introduced an empirical angular distance between two k -variate data vectors based on the number of hyperplanes (the so-called interdirections ) that separate these two points, and proposed a multivariate sign test based on those interdirections. In this paper, we present an analogous concept (namely, lift-interdirections ) to measure the regular distances between data points. The empirical distance between two k -variate data vectors is again determined by the number of hyperplanes that separate these two points; in th…

Affine-invariant rank tests for multivariate independence in independent component models

2016

We consider the problem of testing for multivariate independence in independent component (IC) models. Under a symmetry assumption, we develop parametric and nonparametric (signed-rank) tests. Unlike in independent component analysis (ICA), we allow for the singular cases involving more than one Gaussian independent component. The proposed rank tests are based on componentwise signed ranks, à la Puri and Sen. Unlike the Puri and Sen tests, however, our tests (i) are affine-invariant and (ii) are, for adequately chosen scores, locally and asymptotically optimal (in the Le Cam sense) at prespecified densities. Asymptotic local powers and asymptotic relative efficiencies with respect to Wilks’…

Analyse de la distribution spatiale des implantations humaines : apports et limites d’indicateurs multi-échelles et trans-échelles

2020

As human beings, it is easy for us to judge visually whether a distribution is dispersed or concentrated. However, the quantitative formalization of our impressions is problematic. It depends on the scales of the chosen analysis. This dependence of indicators on scales has changed. It is initially considered as a barrier to knowledge, it now reflects the multi-scale organisation of the distributions studied. The central objective of this thesis is to investigate the limits and contribution of multi-scale and trans-scale indicators to the study of the spatial distributions of human settlements.Spatial analysis aims at comparing spatial distributions to a uniform distribution. The way in whic…

Les chiffres du crime en débat. Pour une exploitation raisonnée des statistiques pénales en sciences sociales

2007

Stochastic algorithms for robust statistics in high dimension

2016

This thesis focus on stochastic algorithms in high dimension as well as their application in robust statistics. In what follows, the expression high dimension may be used when the the size of the studied sample is large or when the variables we consider take values in high dimensional spaces (not necessarily finite). In order to analyze these kind of data, it can be interesting to consider algorithms which are fast, which do not need to store all the data, and which allow to update easily the estimates. In large sample of high dimensional data, outliers detection is often complicated. Nevertheless, these outliers, even if they are not many, can strongly disturb simple indicators like the me…