The LASSO is a widely used statistical methodology for simultaneous estimation and variable selection. In the last years, many authors analyzed this technique from a theoretical and applied point of view. We introduce and study the adaptive LASSO problem for discretely observed ergodic diffusion processes. We prove oracle propertiesalso deriving the asymptotic distribution of the LASSO estimator. Our theoretical framework is based on the random field approach and it applied to more general families of regular statistical experiments in the sense of Ibragimov-Hasminskii (1981).Furthermore, we perform a simulation and real data analysis to provide some evidence on the applicability of this method

Adaptive LASSO-type estimation for ergodic diffusion processes / A. De Gregorio, S.M. Iacus. - Berkeley : Berkeley electronic press, 2010 Apr 01.

Adaptive LASSO-type estimation for ergodic diffusion processes

S.M. Iacus
Ultimo
2010

Abstract

The LASSO is a widely used statistical methodology for simultaneous estimation and variable selection. In the last years, many authors analyzed this technique from a theoretical and applied point of view. We introduce and study the adaptive LASSO problem for discretely observed ergodic diffusion processes. We prove oracle propertiesalso deriving the asymptotic distribution of the LASSO estimator. Our theoretical framework is based on the random field approach and it applied to more general families of regular statistical experiments in the sense of Ibragimov-Hasminskii (1981).Furthermore, we perform a simulation and real data analysis to provide some evidence on the applicability of this method
1-apr-2010
Lasso estimation ; Model selection ; Diffusion processes
Settore SECS-S/01 - Statistica
Settore MAT/06 - Probabilita' e Statistica Matematica
Settore SECS-S/06 - Metodi mat. dell'economia e Scienze Attuariali e Finanziarie
Università degli studi di Milano
http://services.bepress.com/unimi/statistics/art50
Working Paper
Adaptive LASSO-type estimation for ergodic diffusion processes / A. De Gregorio, S.M. Iacus. - Berkeley : Berkeley electronic press, 2010 Apr 01.
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/151472
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact