Bayesian Estimation in Functional-Structural Plant Models with Stochastic Organogenesis

Cédric Loi 1, 2 Paul-Henry Cournède 1, 2, * Samis Trevezas 1, 2
* Corresponding author
2 DIGIPLANTE - Modélisation de la croissance et de l'architecture des plantes
MAS - Mathématiques Appliquées aux Systèmes - EA 4037, CIRAD - Centre de Coopération Internationale en Recherche Agronomique pour le Développement, Inria Saclay - Ile de France, Ecole Centrale Paris
Abstract : In this article, Functional Structural Plant growth Models (FSPMs) with stochastic organogenesis are described in the framework of Jump Markov Models. A Bayesian approach is adopted to estimate uncertain ecophysiological parameters. In particular, two estimation procedures are detailed: the Rao-Blackwellized Particle Filter and the Convolution Particle Filter. These methods are then applied and compared throughout a particular FSPM: the GreenLab model with stochastic organogenesis.
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Cédric Loi, Paul-Henry Cournède, Samis Trevezas. Bayesian Estimation in Functional-Structural Plant Models with Stochastic Organogenesis. 14th Applied Stochastic Models and Data Analysis International Conference (ASMDA 2011), Jun 2011, Rome, Italy. ⟨hal-00653672⟩

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