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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Volume (Year): 100 (2009)
Issue (Month): 8 (September)
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References listed on IDEAS
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- A. Azzalini & A. Capitanio, 1999. "Statistical applications of the multivariate skew normal distribution," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(3), pages 579-602.
- Wong, Wing-Keung & Bian, Guorui, 2005.
"Estimating parameters in autoregressive models with asymmetric innovations,"
Statistics & Probability Letters,
Elsevier, vol. 71(1), pages 61-70, January.
- Wing-Keung Wong & Guorui Bian, 2004. "Estimating Parameters in Autoregressive Models with Asymmetric Innovations," Departmental Working Papers wp0408, National University of Singapore, Department of Economics.
- Alan Hutson, 2004. "Utilizing the Flexibility of the Epsilon-Skew-Normal Distribution for Common Regression Problems," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(6), pages 673-683.
- Reinaldo B. Arellano-Valle & Adelchi Azzalini, 2006. "On the Unification of Families of Skew-normal Distributions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 33(3), pages 561-574.
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