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On goodness-of-fit tests for parametric hypotheses in perturbed dynamical systems using a minimum distance estimator

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  • Maroua Ben Abdeddaiem

    (Université du Maine)

Abstract

We consider the problem of the construction of the goodness-of-fit test in the case of continuous time observations of a diffusion process with small noise. The null hypothesis is parametric and we use a minimum distance estimator of the unknown parameter. We propose an asymptotically distribution free test for this model.

Suggested Citation

  • Maroua Ben Abdeddaiem, 2016. "On goodness-of-fit tests for parametric hypotheses in perturbed dynamical systems using a minimum distance estimator," Statistical Inference for Stochastic Processes, Springer, vol. 19(3), pages 259-287, October.
    • Handle: RePEc:spr:sistpr:v:19:y:2016:i:3:d:10.1007_s11203-016-9132-6
    DOI: 10.1007/s11203-016-9132-6
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    References listed on IDEAS

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    1. M. Kleptsyna & Yu. Kutoyants, 2014. "On asymptotically distribution free tests with parametric hypothesis for ergodic diffusion processes," Statistical Inference for Stochastic Processes, Springer, vol. 17(3), pages 295-319, October.
    2. Ilia Negri & Yoichi Nishiyama, 2009. "Goodness of fit test for ergodic diffusion processes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(4), pages 919-928, December.
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