Les méthodes d'interpolation pour données sur zones

Areal interpolation methods

• Auteur / Autrice : Van Huyen Do
• Direction : Christine Thomas-Agnan, Anne Vanhems
• Type : Thèse de doctorat
• Discipline(s) : Mathématiques
• Date : Soutenance le 15/06/2015
• Etablissement(s) : Toulouse 1
• Ecole(s) doctorale(s) : École doctorale Mathématiques, informatique et télécommunications (Toulouse)
• Partenaire(s) de recherche : Equipe de recherche : Groupe de recherche en économie mathématique et quantitative (Toulouse)

Mots clés

Mots clés contrôlés

Espaces d'interpolation

Mots clés libres

Méthodes d'interpolation

Résumé

Le résumé en français n'a pas été communiqué par l'auteur.

The combination of several socio-economic data bases originating from different administrative sources collected on several different partitions of a geographic zone of interest into administrative units induces the so called areal interpolation problem. This problem is that of allocating the data from a set of source spatial units to a set of target spatial units. At the European level for example, the EU directive ’INSPIRE’, or INfrastructure for Spatial InfoRmation, encourages the states to provide socio-economic data on a common grid to facilitate economic studies across states. In the literature, there are three main types of such techniques: proportional weighting schemes, smoothing techniques and regression based interpolation. We propose a theoretical evaluation of these statistical techniques for the case of count related data. We find extensions of some of these methods to new cases : for example, we extend the ordinary dasymetric weightingmethod to the case of an intensive target variable Y and an extensive auxiliary quantitative variable X and we introduce a scaled version of the Poisson regression method which satisfies the pycnophylactic property. We present an empirical study on an American database as well as an R-package for implementing these methods.