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The Birth–death Processes with Regular Boundary: Stationarity and Quasi-stationarity

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Abstract

For the birth—death Q-matrix with regular boundary, its minimal process and its maximal process are closely related. In this paper, we obtain the uniform decay rate and the quasi-stationary distribution for the minimal process. And via the construction theory, we mainly derive the eigentime identity and the distribution of the fastest strong stationary time (FSST) for the maximal process.

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References

  1. Anderson, W. J.: Continuous-time Markov Chains: An Applications-Oriented Approach. Springer Series in Statistics: Probability and its Applications, Springer, New York, 1991

    Book  Google Scholar 

  2. Billingsley, P.: Convergence of Probability Measures, 2nd Ed., John Wiley & Sons, Inc., New York, 1999

    Book  Google Scholar 

  3. Chen, M. F.: A comment on the book “Continuous-Time Markov Chains” by W. J. Anderson. Chinese J. Appl. Probab. Statist., 12, 55–59 (1996)

    MathSciNet  MATH  Google Scholar 

  4. Chen, M. F.: Analytic proof of dual variational formula for the first eigenvalue in dimension one. Sci. China Ser. A, 42, 805–815 (1999)

    Article  MathSciNet  Google Scholar 

  5. Chen, M. F.: Speed of stability for birth-death processes. Front. Math. China, 5, 379–515 (2010)

    Article  MathSciNet  Google Scholar 

  6. Chen, M. F., Zhang, X.: Isospectral operators. Commun. Math. Stat., 2, 17–32 (2013)

    Article  MathSciNet  Google Scholar 

  7. Collet, P., Martínez, S., San Martín, J.: Quasi-Stationary Distributions. Markov Chains, Diffusions and Dynamical Systems. Probability and Its Applications (New York), Springer, Heidelberg, 2013

    MATH  Google Scholar 

  8. Darroch, J. N., Seneta, E.: On quasi-stationary distributions in absorbing continuous-time finite Markov chains. J. Appl. Probab., 4, 192–196 (1967)

    Article  MathSciNet  Google Scholar 

  9. Ethier, S. N., Kurtz, T. G.: Markov Processes: Characterization and Convergence. Wiley Series in Probability and Mathematical Statistics: Probability and Mathematical Statistics. John Wiley & Sons, Inc., New York, 1986

    Book  Google Scholar 

  10. Feller, W.: The birth and death processes as diffusion processes. J. Math. Pures Appl., 38, 301–345 (1959)

    MathSciNet  MATH  Google Scholar 

  11. Fill, J. A.: Time to stationary for a continuous-time Markov chains. Probab. Engrg. Inform. Sci., 5, 45–47 (1991)

    Article  MathSciNet  Google Scholar 

  12. Fill, J. A.: Strong stationary duality for continuous-time Markov chains Part I: Theory. J. Theoret. Probab., 5, 45–70 (1992)

    Article  MathSciNet  Google Scholar 

  13. Fill, J. A.: On hitting times and fastest strong stationary times for skip-free and more general chains. J. Theoret. Probab., 22, 587–600 (2009)

    Article  MathSciNet  Google Scholar 

  14. Gao, W. J., Mao, Y. H.: Quasi-stationary distribution for the birth-death process with exit boundary. J. Math. Anal. Appl., 427, 114–125 (2015)

    Article  MathSciNet  Google Scholar 

  15. Gong, Y., Mao, Y. H., Zhang, C.: The hitting time distribution for a denumerable birth-death Process. J. Theoret. Probab., 25, 950–980 (2012)

    Article  MathSciNet  Google Scholar 

  16. Kallenberg, O.: Foundations of Modern Probability, 2nd Ed. Probability and Its Applications, Springer-Verlag, New York, 2002

    MATH  Google Scholar 

  17. Karlin, S., McGregor, J.: A characterization of birth and death processes. Proc. Natl. Acad. Sci. USA, 45, 375–379 (1959)

    Article  MathSciNet  Google Scholar 

  18. Kijima, M., Nair, M. G., Pollett, P. K. et al.: Limiting conditional distributions for birth—death processes. Adv. in Appl. Probab., 29, 185–204 (1997)

    Article  MathSciNet  Google Scholar 

  19. Kurtz, T. G.: Semigroups of conditioned shifts and approximation of Markov processes. Ann. Probab., 3, 618–642 (1975)

    Article  MathSciNet  Google Scholar 

  20. Mao, Y. H.: The Eigentime identity for continuous-time ergodic Markov chains. J. Appl. Probab., 41, 1071–1080 (2004)

    Article  MathSciNet  Google Scholar 

  21. Mao, Y. H., Zhang, C.: Hitting time distributions for birth-death processes with bilateral absorbing boundaries. Probab. Engrg. Inform. Sci., 31(3), 345–356 (2017)

    Article  MathSciNet  Google Scholar 

  22. Mao, Y. H., Zhang, C.: Uniform convergence rate for the birth-death processes. Markov Processes Relat. Fields, 23, 467–483 (2017)

    MathSciNet  MATH  Google Scholar 

  23. Pollett, P. K.: Quasi-stationary distributions: A bibliography. Available at http://www.maths.uq.edu.au/pkp/papers/qsds

  24. van Doorn, E. A.: Quasi-stationary distributions and convergence to quasi-stationarity of birth—death processes. Adv. in Appl. Probab., 23, 683–700 (1991)

    Article  MathSciNet  Google Scholar 

  25. van Dorn, E. A.: An orthogonal-polynomial approach to first-hitting times of birth-death processes. J. Theor. Probab., 30, 594–607 (2017)

    Article  MathSciNet  Google Scholar 

  26. van Doorn, E. A., Pollett, P. K.: Quasi-stationary distributions for discrete-state models. European J. Oper. Res., 230, 1–14 (2013)

    Article  MathSciNet  Google Scholar 

  27. Varadhan, S. R. S.: Stochastic Processes. Courant Lecture Notes in Mathematics, Vol. 16, Amer. Math. Soc., Providence, RI, 2007

    Google Scholar 

  28. Wang, Z. K., Yang, X. Q.: Birth and Death Processes and Markov Processes. Berlin: Springer-Verlag; Beijing: Science Press Beijing, 1992

    MATH  Google Scholar 

  29. Yang, X. Q.: The Construction Theory of Denumerable Markov Processes. Wiley Series in Probability and Mathematical Statistics: Probability and Mathematical Statistics. John Wiley & Sons, Inc., Chichester, 1990

    Google Scholar 

  30. Zhang, H. J., Chen A. Y., Lin, X. et al.: Strong ergodicity of monotone transition functions. Statist. Probab. Lett., 55, 63–69 (2001)

    Article  MathSciNet  Google Scholar 

  31. Zhang, H. J., Lin, X., Hou, Z. T.: Polynomial uniform convergence for standard transition functions (in Chinese). Chinese Ann. Math. Ser. A, 21, 351–356 (2000)

    Article  MathSciNet  Google Scholar 

  32. Zhang, Y. H.: Strong ergodicity for single birth processes. J. Appl. Probab., 38, 270–277 (2001)

    Article  MathSciNet  Google Scholar 

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Acknowledgements

The authors would like to thank the reviewers for their helpful comments.

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Correspondence to Chi Zhang.

Additional information

Supported by the National Natural Science Foundation of China (Grant Nos. 11501531, 11701265, 11771047)

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Gao, W.J., Mao, Y.H. & Zhang, C. The Birth–death Processes with Regular Boundary: Stationarity and Quasi-stationarity. Acta. Math. Sin.-English Ser. 38, 890–906 (2022). https://doi.org/10.1007/s10114-022-0567-y

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  • DOI: https://doi.org/10.1007/s10114-022-0567-y

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