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Estimation for Continuous Branching Processes

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  • Ludger Overbeck

Abstract

The maximum‐likelihood estimator for the curved exponential family given by continuous branching processes with immigration is investigated. These processes originated from population biology but also model the dynamics of interest rates and development of the state of technology in economics. It is proved that in contrast to branching processes with discrete space and/or time the MLE gives a unified approach to the inference. In order to include singular subdomains of the parameter space we modify the MLE slightly. Consistency and asymptotic normality for the MLE are considered. Concerning the asymptotic theory of the experiments, all three properties LAQ, LAN, and LAMN occur for different submodels

Suggested Citation

  • Ludger Overbeck, 1998. "Estimation for Continuous Branching Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 25(1), pages 111-126, March.
    • Handle: RePEc:bla:scjsta:v:25:y:1998:i:1:p:111-126
    DOI: 10.1111/1467-9469.00092
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    Citations

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    Cited by:

    1. Demni, N. & Zani, M., 2009. "Large deviations for statistics of the Jacobi process," Stochastic Processes and their Applications, Elsevier, vol. 119(2), pages 518-533, February.
    2. Pap Gyula & Szabó Tamás T., 2016. "Change detection in the Cox–Ingersoll–Ross model," Statistics & Risk Modeling, De Gruyter, vol. 33(1-2), pages 21-40, September.
    3. Matyas Barczy & Leif Doering & Zenghu Li & Gyula Pap, 2013. "Parameter estimation for a subcritical affine two factor model," Papers 1302.3451, arXiv.org, revised Apr 2014.
    4. Mohamed Ben Alaya & Ahmed Kebaier & Ngoc Khue Tran, 2020. "Local asymptotic properties for Cox‐Ingersoll‐Ross process with discrete observations," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(4), pages 1401-1464, December.
    5. Matyas Barczy & Leif Doering & Zenghu Li & Gyula Pap, 2012. "On parameter estimation for critical affine processes," Papers 1210.1866, arXiv.org, revised Mar 2013.
    6. Zani, Marguerite, 2002. "Large deviations for squared radial Ornstein-Uhlenbeck processes," Stochastic Processes and their Applications, Elsevier, vol. 102(1), pages 25-42, November.
    7. Marie Roy de Chaumaray, 2018. "Moderate deviations for parameters estimation in a geometrically ergodic Heston process," Statistical Inference for Stochastic Processes, Springer, vol. 21(3), pages 553-567, October.
    8. Matyas Barczy & Mohamed Ben Alaya & Ahmed Kebaier & Gyula Pap, 2015. "Asymptotic behavior of maximum likelihood estimators for a jump-type Heston model," Papers 1509.08869, arXiv.org, revised May 2018.
    9. Huang, Jianhui & Ma, Chunhua & Zhu, Cai, 2011. "Estimation for discretely observed continuous state branching processes with immigration," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 1104-1111, August.
    10. Gao, Fuqing & Jiang, Hui, 2009. "Moderate deviations for squared radial Ornstein-Uhlenbeck process," Statistics & Probability Letters, Elsevier, vol. 79(11), pages 1378-1386, June.
    11. Matyas Barczy & Gyula Pap, 2013. "Asymptotic properties of maximum likelihood estimators for Heston models based on continuous time observations," Papers 1310.4783, arXiv.org, revised Jun 2015.
    12. Alfonsi, Aurélien & Kebaier, Ahmed & Rey, Clément, 2016. "Maximum likelihood estimation for Wishart processes," Stochastic Processes and their Applications, Elsevier, vol. 126(11), pages 3243-3282.
    13. Li, Zenghu & Ma, Chunhua, 2015. "Asymptotic properties of estimators in a stable Cox–Ingersoll–Ross model," Stochastic Processes and their Applications, Elsevier, vol. 125(8), pages 3196-3233.
    14. Barczy, Mátyás & Ben Alaya, Mohamed & Kebaier, Ahmed & Pap, Gyula, 2018. "Asymptotic properties of maximum likelihood estimator for the growth rate for a jump-type CIR process based on continuous time observations," Stochastic Processes and their Applications, Elsevier, vol. 128(4), pages 1135-1164.
    15. Matyas Barczy & Mohamed Ben Alaya & Ahmed Kebaier & Gyula Pap, 2016. "Asymptotic properties of maximum likelihood estimator for the growth rate for a jump-type CIR process based on continuous time observations," Papers 1609.05865, arXiv.org, revised Aug 2017.
    16. Matyas Barczy & Mohamed Ben Alaya & Ahmed Kebaier & Gyula Pap, 2017. "Asymptotic properties of maximum likelihood estimator for the growth rate of a stable CIR process based on continuous time observations," Papers 1711.02140, arXiv.org, revised Feb 2019.

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