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On Lasso-type estimation for dynamical systems with small noise

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  • Stefano Maria IACUS

Abstract

We consider a dynamical system with small noise where the drift is parametrized by afinite dimensional parameter. For this model we consider minimum distance estimation fromcontinuous time observations under some penalty imposed on the parameters in the spirit of the Lasso approach. This approach allows for simultaneous estimation and model selection for this model.

Suggested Citation

  • Stefano Maria IACUS, 2010. "On Lasso-type estimation for dynamical systems with small noise," Departmental Working Papers 2010-12, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    • Handle: RePEc:mil:wpdepa:2010-12
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    File URL: http://wp.demm.unimi.it/files/wp/2010/DEMM-2010_012wp.pdf
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    References listed on IDEAS

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    3. Kutoyants, Y. & Pilibossian, P., 1994. "On minimum L1-norm estimate of the parameter of the Ornstein--Uhlenbeck process," Statistics & Probability Letters, Elsevier, vol. 20(2), pages 117-123, May.
    4. Pollard, David, 1991. "Asymptotics for Least Absolute Deviation Regression Estimators," Econometric Theory, Cambridge University Press, vol. 7(2), pages 186-199, June.
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