Parameter identification for the Hermite Ornstein-Uhlenbeck process
DOI10.1007/s11203-020-09219-zzbMath1448.60118OpenAlexW3033402842MaRDI QIDQ2194047
Obayda Assaad, Ciprian A. Tudor
Publication date: 25 August 2020
Published in: Statistical Inference for Stochastic Processes (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11203-020-09219-z
parameter estimationasymptotic normalityfractional Brownian motionOrnstein-Uhlenbeck processstrong consistencymultiple Wiener-Itô integralsHermite processHurst index estimation
Asymptotic properties of parametric estimators (62F12) Fractional processes, including fractional Brownian motion (60G22) Stochastic calculus of variations and the Malliavin calculus (60H07)
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Cites Work
- A Fourier analytic approach to pathwise stochastic integration
- Stochastic evolution equations with Volterra noise
- A wavelet analysis of the Rosenblatt process: chaos expansion and estimation of the self-similarity parameter
- Dissipative stochastic evolution equations driven by general Gaussian and non-Gaussian noise
- Hurst index estimation in stochastic differential equations driven by fractional Brownian motion
- Variations and estimators for self-similarity parameters via Malliavin calculus
- Central limit theorems for non-linear functionals of Gaussian fields
- Fractional {O}rnstein-{U}hlenbeck processes
- Statistical inference for Vasicek-type model driven by Hermite processes
- Behavior with respect to the Hurst index of the Wiener Hermite integrals and application to SPDEs
- Self-similarity parameter estimation and reproduction property for non-Gaussian Hermite processes
- Stochastic Processes and Long Range Dependence
- Analysis of Variations for Self-similar Processes
- Normal Approximations with Malliavin Calculus
- The Malliavin Calculus and Related Topics
- Lp-valued stochastic convolution integral driven by Volterra noise
- Non-central limit theorems for quadratic functionals of Hermite-driven long memory moving average processes
- Limiting measure and stationarity of solutions to stochastic evolution equations with Volterra noise
- The linear stochastic heat equation with Hermite noise
- Limit behavior of the Rosenblatt Ornstein–Uhlenbeck process with respect to the Hurst index
- Long-Range Dependence and Self-Similarity
- Wiener Integrals with Respect to the Hermite Process and a Non-Central Limit Theorem
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