A bivariate beta-gamma autoregressive process (BVBGAR(1))

Communications in Statistics - Theory and Methods

Volumn 38, Issue 7, 2009, Pages 1113-1131

  Bakouch, Hassan S ^a   Ristić, Miroslav M ^b  

^a TANTA UNIVERSITY   (Egypt)

^b UNIVERSITY OF NI   (Serbia)

Author keywords

Autocovariance matrix; Beta Gamma transformation; Bivariate autoregressive process; Estimation; Gamma distribution; Spectral density matrix; Stationary process

Indexed keywords

AUTO REGRESSIVE PROCESS; AUTOCOVARIANCE MATRICES; BIVARIATE; GAMMA DISTRIBUTION; SPECTRAL DENSITY MATRIX; STATIONARY PROCESS;

METHOD OF MOMENTS; NUMERICAL ANALYSIS; PROBABILITY DISTRIBUTIONS; SPECTRAL DENSITY;

QUANTUM THEORY;

EID: 71649113711     PISSN: 03610926     EISSN: 1532415X     Source Type: Journal    
DOI: 10.1080/03610920802376330     Document Type: Article

References (21)

1. Al-Osh, M. A., Alzaid, A. A. (1993). Some Gamma processes based on the Dirichlet-Gamma transformation. Commun. Statist. Stoch. Mod. 9:123-143.
2. Brillinger, D. R. (1975). Time Series: Data Analysis and Theory. New York: Holt, Rinehart and Winston.
3. Dewald, L. S., Lewis, P. A. W., McKenzie, E. (1989). A bivariate first-order autoregressive time series model in exponential variables (BEAR(1)). Manage. Sci. 35:1236-1246.
4. Fodor, I. K. (1999). Spectrum Estimation in Helioseismology. Ph.D. thesis, University of California, Berkeley.
5. Gaver, D. P., Lewis, P. A. W. (1980). First-order autoregressive Gamma sequences and point processes. Adv. Appl. Probab. 12:727-745.
6. Gourieroux, C., Jasiak, J. (2006). Autoregressive Gamma processes. J. Forecasting 25: 125-152.
7. Lawrance, A. J. (1982). The innovation distribution of a Gamma distributed autoregressive process. Scand. J. Statist. 9:234-236.
8. Lewis, P. A. W. (1983). Generating negatively correlated Gamma variates using the Beta-Gamma transformation. Proc. 1983 Winter Simul. Conf. New York: IEEE Press, pp. 175-176.
9. Lewis, P. A. W., McKenzie, E., Hugus, D. K. (1989). Gamma processes. Commun. Statist. Stoch. Mod. 5:1-30.
10. McCoy, E. J. (1994). Some New Statistical Approaches to the Analysis of Long Memory Processes. Ph.D. thesis, Imperial College, University of London.
11. McKenzie, E. (1982). Product autoregression: a time series characterization of the Gamma distribution. J. Appl. Probab. 19:463-468.
12. Nicholls, D. F., Quinn, B. G. (1982). Random Coefficient Autoregressive Models: An Introduction. Heidelberg: Springer-Verlag.
13. Riedel, K. S., Sidorenko, A. (1995). Minimum bias multiple taper spectral estimation. IEEE Trans. Sig. Process. 43:188-195.
14. Ristíc, M. M. (2005). A Beta-Gamma autoregressive process of the second-order (BGAR(2)). Statist. Probab. Lett. 73:403-410.
15. Ristić, M. M., Popović, B. č . (2003). A bivariate uniform autoregressive process. Ann. Inst. Statist. Math. 55:797-802.
16. Sim, C. H. (1986). Simulation of Weibull and Gamma autoregressive stationary process. Commun. Statist. Simul. Comput. 15:1141-1146.
17. Sim, C. H. (1990). First-order autoregressive models for Gamma and exponential processes. J. Appl. Probab. 27:325-332.
18. Teamah, A. A. M., Bakouch, H. S. (2004a). Asymptotic statistical properties of spectral estimates with different tapers for discrete time processes. Appl. Math. Computat. 150:681-695.
19. Teamah, A. A. M., Bakouch, H. S. (2004b). Multitaper multivariate spectral estimators of time series with distorted observations. Int. J. Pure Appl. Math. 14:47-59.
20. Thomson, D. J. (1982). Spectrum estimation and harmonic analysis. Proc. IEEE 70:1055-1096.
21. Walden, A. T., McCoy, E. J., Percival, D. B. (1994). The variance of multitaper spectrum estimates for real Gaussian processes. IEEE Trans. Sig. Process. 42:479-482.