Estimation of Discrete Partially Directed Acyclic Graphical Models in Multitype Branching Processes

Pierre Fernique; Jean-Baptiste Durand; Yann Guédon

Estimation of Discrete Partially Directed Acyclic Graphical Models in Multitype Branching Processes

Pierre Fernique ^{1, 2} Jean-Baptiste Durand ^{2, 3} Yann Guédon ^{1, 2}

1 UMR AGAP - Amélioration génétique et adaptation des plantes méditerranéennes et tropicales

2 VIRTUAL PLANTS - Modeling plant morphogenesis at different scales, from genes to phenotype

CRISAM - Inria Sophia Antipolis - Méditerranée , INRA - Institut National de la Recherche Agronomique, UMR AGAP - Amélioration génétique et adaptation des plantes méditerranéennes et tropicales

3 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems

Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble

Abstract : We address the inference of discrete-state models for tree-structured data. Our aim is to introduce parametric multitype branching processes that can be efficiently estimated on the basis of data of limited size. Each generation distribution within this macroscopic model is modeled by a partially directed acyclic graphical model. The estimation of each graphical model relies on a greedy algorithm for graph selection. We present an algorithm for discrete graphical model which is applied on multivariate count data. The proposed modeling approach is illustrated on plant architecture datasets.

Keywords : multivariate count data branching process plant architecture Partially directed graphical model graph selection multivariate discrete distribu-tion tree pattern

Document type :

Conference papers

Domain :

Statistics [stat]

Computer Science [cs] / Modeling and Simulation

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https://hal.inria.fr/hal-01084524
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Submitted on : Wednesday, November 19, 2014 - 2:36:17 PM
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FerniqueDurandGuedon2014b.pdf

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