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Strong consistency of the maximum quasi-likelihood estimator in quasi-likelihood nonlinear models with stochastic regression

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  • Xia, Tian
  • Jiang, Xuejun
  • Wang, Xueren

Abstract

This paper proposes some mild regularity conditions analogous to those given by Wu (1981) and Chang (1999). On the basis of the proposed regularity conditions, the strong consistency as well as convergence rate for maximum quasi-likelihood estimator (MQLE) is obtained in quasi-likelihood nonlinear models (QLNMs) with stochastic regression.

Suggested Citation

  • Xia, Tian & Jiang, Xuejun & Wang, Xueren, 2015. "Strong consistency of the maximum quasi-likelihood estimator in quasi-likelihood nonlinear models with stochastic regression," Statistics & Probability Letters, Elsevier, vol. 103(C), pages 37-45.
    • Handle: RePEc:eee:stapro:v:103:y:2015:i:c:p:37-45
    DOI: 10.1016/j.spl.2015.04.016
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    References listed on IDEAS

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    1. Bo-Cheng Wei & Jian-Qing Shi & Wing-Kam Fung & Yue-Qing Hu, 1998. "Testing for Varying Dispersion in Exponential Family Nonlinear Models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 50(2), pages 277-294, June.
    2. Chang, Yuan-chin Ivan, 1999. "Strong consistency of maximum quasi-likelihood estimate in generalized linear models via a last time," Statistics & Probability Letters, Elsevier, vol. 45(3), pages 237-246, November.
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