Inference for conditioned Galton-Watson trees from their Harris path

Romain Azaïs 1, 2 Alexandre Genadot 3 Benoît Henry 4, 1
1 Probabilités et statistiques
IECL - Institut Élie Cartan de Lorraine
2 BIGS - Biology, genetics and statistics
Inria Nancy - Grand Est, IECL - Institut Élie Cartan de Lorraine
3 CQFD - Quality control and dynamic reliability
IMB - Institut de Mathématiques de Bordeaux, Inria Bordeaux - Sud-Ouest
4 TOSCA - TO Simulate and CAlibrate stochastic models
CRISAM - Inria Sophia Antipolis - Méditerranée , IECL - Institut Élie Cartan de Lorraine : UMR7502
Abstract : Tree-structured data naturally appear in various fields, particularly in biology where plants and blood vessels may be described by trees, but also in computer science because XML documents form a tree structure. This paper is devoted to the estimation of the relative scale of ordered trees that share the same layout. The theoretical study is achieved for the stochastic model of conditioned Galton-Watson trees. New estimators are introduced and their consistency is stated. A comparison is made with an existing approach of the literature. A simulation study shows the good behavior of our procedure on finite-sample sizes and from missing or noisy data. An application to the analysis of revisions of Wikipedia articles is also considered through real data.
Type de document :
Pré-publication, Document de travail
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Contributeur : Romain Azaïs <>
Soumis le : mardi 20 juin 2017 - 09:29:14
Dernière modification le : mardi 17 avril 2018 - 09:04:55
Document(s) archivé(s) le : vendredi 15 décembre 2017 - 19:22:23


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  • HAL Id : hal-01360650, version 2
  • ARXIV : 1609.01057



Romain Azaïs, Alexandre Genadot, Benoît Henry. Inference for conditioned Galton-Watson trees from their Harris path. 2017. 〈hal-01360650v2〉



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