Y
Yves Tillé
Researcher at University of Neuchâtel
Publications - 83
Citations - 1580
Yves Tillé is an academic researcher from University of Neuchâtel. The author has contributed to research in topics: Sampling (statistics) & Population. The author has an hindex of 20, co-authored 79 publications receiving 1356 citations. Previous affiliations of Yves Tillé include Université libre de Bruxelles & École Normale Supérieure.
Papers
More filters
Journal ArticleDOI
Some Thoughts on Official Statistics and its Future (with discussion)
Yves Tillé,Marc Debusschere,Henri Luomaranta,Martin Axelson,Eva Elvers,Anders Holmberg,Richard Valliant +6 more
TL;DR: In this article , the state of statistical science and its evolution in the production systems of official statistics are discussed. And the potential of valorization of big data in official statistics is examined.
Journal ArticleDOI
Some Solutions Inspired by Survey Sampling Theory to Build Effective Clinical Trials
TL;DR: In this paper , the cube method is combined with multivariate matching to balance the mean of the covariates in the test and control groups, and a set of simulations is carried out in order to evaluate the different methods.
Estimation de la précision d’évolutions dans les enquêtes répétées, application à l’enquête suisse sur la valeur ajoutée
Lionel Qualité,Yves Tillé +1 more
TL;DR: In this paper, a méthode for estimating variance of estimateurs des évolutions is proposed, which prend en compte toutes les composantes de ceux-ci : le plan de sondage, le traitement des non-réponses, the traitement of grosses entreprises, the corrélation de la non-reponse d'une vague à l'autre, l'effet dû à l’utilisation d'un panel, the robustification and le calage au
Posted Content
Stream Sampling with Immediate Decision
TL;DR: In this paper, the authors introduce a method to select a random sample from a stream by deciding on each sampling unit immediately after observing it, which can be applied to unequal as well as equal probability sampling.
Journal ArticleDOI
Spatial Spread Sampling Using Weakly Associated Vectors.
Raphaël Jauslin,Yves Tillé +1 more
TL;DR: In this paper, the authors proposed a new method for selecting well-spread samples from a finite spatial population with equal or unequal inclusion probabilities, which is based on the definition of a spatial structure by using a stratification matrix.