Bayesian Estimation in Functional-Structural Plant Models with Stochastic Organogenesis
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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