We consider a dynamical system with small noise for which the drift is parametrized by a finite dimensional parameter. For this model, we consider minimum distance estimation from continuous time observations under lp-penalty imposed on the parameters in the spirit of the Lasso approach, with the aim of simultaneous estimation and model selection. We study the consistency and the asymptotic distribution of these Lasso-type estimators for different values of p. For p = 1, we also consider the adaptive version of the Lasso estimator and establish its oracle properties.
On penalized estimation for dynamical systems with small noise / De Gregorio, Alessandro; Iacus, Stefano Maria. - In: ELECTRONIC JOURNAL OF STATISTICS. - ISSN 1935-7524. - ELETTRONICO. - 12:1(2018), pp. 1614-1630. [10.1214/18-EJS1436]
On penalized estimation for dynamical systems with small noise
De Gregorio, Alessandro;
2018
Abstract
We consider a dynamical system with small noise for which the drift is parametrized by a finite dimensional parameter. For this model, we consider minimum distance estimation from continuous time observations under lp-penalty imposed on the parameters in the spirit of the Lasso approach, with the aim of simultaneous estimation and model selection. We study the consistency and the asymptotic distribution of these Lasso-type estimators for different values of p. For p = 1, we also consider the adaptive version of the Lasso estimator and establish its oracle properties.| File | Dimensione | Formato | |
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