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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
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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Submitted on : Tuesday, December 20, 2011 - 2:34:04 AM
Last modification on : Friday, February 4, 2022 - 3:30:23 AM
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  • HAL Id : hal-00653672, version 1



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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