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Nonparametric Estimation of Trend for Stochastic Processes Driven by G-Brownian Motion with Small Noise

Author

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  • Xuekang Zhang

    (Ministry of Education, Anhui Polytechnic University)

  • Shounian Deng

    (Ministry of Education, Anhui Polytechnic University)

  • Weiyin Fei

    (Ministry of Education, Anhui Polytechnic University)

Abstract

The present paper deals with the problem of nonparametric estimation of the trend for stochastic processes driven by G-Brownian motion with small noise. The consistency, the bound on the rate of convergence, and the asymptotic distribution of the nonparametric estimator are studied. Finally, a numerical example is given to verify our theoretical results.

Suggested Citation

  • Xuekang Zhang & Shounian Deng & Weiyin Fei, 2023. "Nonparametric Estimation of Trend for Stochastic Processes Driven by G-Brownian Motion with Small Noise," Methodology and Computing in Applied Probability, Springer, vol. 25(2), pages 1-14, June.
    • Handle: RePEc:spr:metcap:v:25:y:2023:i:2:d:10.1007_s11009-023-10045-y
    DOI: 10.1007/s11009-023-10045-y
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    References listed on IDEAS

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    3. M. Mishra & B. Prakasa Rao, 2011. "Nonparametric estimation of trend for stochastic differential equations driven by fractional Brownian motion," Statistical Inference for Stochastic Processes, Springer, vol. 14(2), pages 101-109, May.
    4. Gao, Fuqing, 2009. "Pathwise properties and homeomorphic flows for stochastic differential equations driven by G-Brownian motion," Stochastic Processes and their Applications, Elsevier, vol. 119(10), pages 3356-3382, October.
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