Workshop on Statistical Methods for Dynamic
Vancouver, June 4-6 2009
System Models
We propose a semi-parametric model for autonomous nonlinear dynamical systems and devise an estimation procedure for model fitting. This model incorporates subject-specific effects and can be viewed as a nonlinear semi-parametric mixed effects model. We also propose a computationally efficient model selection procedure. We show by simulation studies that the proposed estimation as well as model selection procedures can efficiently handle sparse noisy measurements. Finally, we apply the proposed method on a plant growth data used to study cell division rates within meristems of maize roots under two different experimental conditions.
Co-authors: Debashis Paul, Prabir Burman.
Semiparametric modelling of autonomous nonlinear dynamical systems with applications
