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  Advances and Applications in Statistics  
 ISSN: 0972-3617
 
 
 

     Advances and Applications in Statistics
    Volume 8, Issue 2, Pages 219 - 246 (April 2008)


MIXTURE PERIODIC AUTOREGRESSION WITH PERIODIC ARCH ERRORS

Mohamed Bentarzi (Algeria) and Fayçal Hamdi (Algeria)

Received October 6, 2007

References:



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[3] R. Dahlhaus and S. Subba Rao, Statistical inference for time-varying ARCH processes, J. Ann. Statist. 34 (2006), 1075-1114.

[4] A. P. Dempster, N. M. Laird and D. B. Rubin, Maximum likelihood from incomplete data via the EM algorithm (with discussion), J. Roy. Statist. Soc. B 39 (1977), 1-38.

[5] R. Engle, Autoregressive conditional heteroscedasticity with estimates of the variance of the UK inflation, Econometrica 50 (1982), 987-1008.

[6] P. H. Franses and R. Paap, Modeling day-of-the-week seasonality in the S and P 500 index, Appl. Financial Economics 10 (2000), 483-488.

[7] N. D. Le, R. D. Martin and A. E. Raftery, Modeling flat stretches, bursts, and outliers in time series using mixture transition distribution models, J. Amer. Statist. Assoc. 91 (1996), 1504-1514.

[8] Q. Shao, Mixture periodic autoregressive time series models, Statist. Probab. Lett. 76 (2006), 609-618.

[9] C. S. Wong and W. K. Li, On a mixture autoregressive model, J. Roy. Statist. Soc. Ser. B 62 (2000), 95-115.

[10] C. S. Wong and W. K. Li, On a mixture autoregressive conditional heteroscedastic model, J. Amer. Statist. Assoc. 96 (2001), 982-995.

[11] Z. Zhang, W. K. Li and K. C. Yuen, On a mixture GARCH time-series model, J. Time Ser. Anal. 27 (2006), 577-597.

Keywords and phrases: mixture periodic autoregressive conditionally heteroskedastic models, periodically correlated process, periodically stationary condition, EM algorithm.

 


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