Semiparametric modeling of autonomous nonlinear dynamical systems with application to plant growth

We propose a semi-parametric model for autonomous nonlinear dynamical systems and devise an estimation procedure for model fltting. This model incorporates subject-speciflc efiects and can be viewed as a nonlinear semi-parametric mixed efiects model. We also propose a computationally e‐cient model selection procedure. We show by simulation studies that the proposed estimation as well as model selection procedures can e‐ciently handle sparse and noisy measurements. Finally, we apply the proposed method to a plant growth data used to study growth displacement rates within meristems of maize roots under two difierent experimental conditions.

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