The multivariate method of simulated quantiles (MMSQ) is proposed as a likelihood–free alternative to indirect inference procedures that does not rely on an auxiliary model specification and its asymptotic properties are established. As a further improvement we introduce the Smoothly clipped absolute deviation (SCAD1 –penalty into the MMSQ objective function in order to achieve sparse estimation of the scaling matrix.We extend the asymptotic theory and we show that the sparse– MMSQ estimator enjoys the oracle properties under mild regularity conditions. The method is applied to estimate the parameters of the Skew Elliptical Stable distribution

Estimation and Inference of Skew–Stable distributions using the Multivariate Method of Simulated Quantiles / Stolfi, Paola; Bernardi, Mauro; Petrella, Lea. - ELETTRONICO. - (2017), pp. 955-960. (Intervento presentato al convegno SIS 2017 Statistics and Data Science: new challenges, new generations tenutosi a Firenze).

Estimation and Inference of Skew–Stable distributions using the Multivariate Method of Simulated Quantiles

Lea Petrella
2017

Abstract

The multivariate method of simulated quantiles (MMSQ) is proposed as a likelihood–free alternative to indirect inference procedures that does not rely on an auxiliary model specification and its asymptotic properties are established. As a further improvement we introduce the Smoothly clipped absolute deviation (SCAD1 –penalty into the MMSQ objective function in order to achieve sparse estimation of the scaling matrix.We extend the asymptotic theory and we show that the sparse– MMSQ estimator enjoys the oracle properties under mild regularity conditions. The method is applied to estimate the parameters of the Skew Elliptical Stable distribution
2017
SIS 2017 Statistics and Data Science: new challenges, new generations
Directional quantiles; Sparse regularisation; Skew Elliptical Stable distribution
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Estimation and Inference of Skew–Stable distributions using the Multivariate Method of Simulated Quantiles / Stolfi, Paola; Bernardi, Mauro; Petrella, Lea. - ELETTRONICO. - (2017), pp. 955-960. (Intervento presentato al convegno SIS 2017 Statistics and Data Science: new challenges, new generations tenutosi a Firenze).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1016378
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