Estimation of autoregressive models with epsilon-skew-normal innovations

A non-Gaussian autoregressive model with epsilon-skew-normal innovations is introduced. Moments and maximum likelihood estimators of the parameters are proposed and their limit distributions are derived. Monte Carlo simulation results are analysed and the model is fitted to a real time series.

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Year of publication:	2009
Authors:	Bondon, Pascal
Published in:	Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 100.2009, 8, p. 1761-1776
Publisher:	Elsevier
Keywords:	Non-Gaussian time series Autoregression Maximum likelihood estimation Skewness Skew-normal distribution

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005006449