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Large deviations inequalities for the maximum likelihood estimator and the Bayes estimators in nonlinear stochastic differential equations

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  • Bishwal, J. P. N.

Abstract

Exponential bounds on the large deviation probability of the maximum likelihood estimator and the Bayes estimators of the parameter appearing nonlinearly in the drift coefficient of homogeneous Itô's stochastic differential equations are obtained under some regularity conditions.

Suggested Citation

  • Bishwal, J. P. N., 1999. "Large deviations inequalities for the maximum likelihood estimator and the Bayes estimators in nonlinear stochastic differential equations," Statistics & Probability Letters, Elsevier, vol. 43(2), pages 207-215, June.
    • Handle: RePEc:eee:stapro:v:43:y:1999:i:2:p:207-215
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    References listed on IDEAS

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    1. Prakasa Rao, B. L. S., 1984. "On the exponential rate of convergence of the least squares estimator in the nonlinear regression model with Gaussian errors," Statistics & Probability Letters, Elsevier, vol. 2(3), pages 139-142, May.
    2. Prakasa Rao, B. L. S., 1984. "The rate of convergence of the least squares estimator in a non-linear regression model with dependent errors," Journal of Multivariate Analysis, Elsevier, vol. 14(3), pages 315-322, June.
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    Cited by:

    1. Bishwal, J. P. N., 2001. "Accuracy of normal approximation for the maximum likelihood estimator and Bayes estimators in the Ornstein-Uhlenbeck process using random normings," Statistics & Probability Letters, Elsevier, vol. 52(4), pages 427-439, May.
    2. Zhang, Pu & Xiao, Wei-lin & Zhang, Xi-li & Niu, Pan-qiang, 2014. "Parameter identification for fractional Ornstein–Uhlenbeck processes based on discrete observation," Economic Modelling, Elsevier, vol. 36(C), pages 198-203.

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