Estimating the order of mean-square derivatives with quadratic variations
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Publication:453781
DOI10.1007/s11203-011-9055-1zbMath1274.62561OpenAlexW1980796273MaRDI QIDQ453781
Publication date: 28 September 2012
Published in: Statistical Inference for Stochastic Processes (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11203-011-9055-1
Gaussian processes (60G15) Non-Markovian processes: estimation (62M09) Sample path properties (60G17)
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Cites Work
- Unnamed Item
- Average case complexity of weighted approximation and integration over \(\mathbb R_{+}\)
- Assessing the number of mean square derivatives of a Gaussian process
- Sojourns and extremes of Gaussian processes
- Uniform reconstruction of Gaussian processes
- Quadratic variations and estimation of the local Hölder index of a Gaussian process
- Average-case analysis of numerical problems
- Optimal designs for weighted approximation and integration of stochastic processes on \([0,\infty)\)
- A note on extreme values of locally stationary Gaussian processes
- Spline approximation of random processes and design problems
- A Strong Limit Theorem for Gaussian Processes
- A New Limit Theorem for Stochastic Processes with Gaussian Increments
- A note on the prediction error for small time lags into the future (Corresp.)
- Prediction of level crossings for normal processes containing deterministic components
- A Bound on Tail Probabilities for Quadratic Forms in Independent Random Variables
