Assessing the number of mean square derivatives of a Gaussian process
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Publication:952829
DOI10.1016/j.spa.2007.10.011zbMath1151.60324OpenAlexW1964277034MaRDI QIDQ952829
Publication date: 14 November 2008
Published in: Stochastic Processes and their Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.spa.2007.10.011
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Gaussian processes (60G15) Sample path properties (60G17) Rate of convergence, degree of approximation (41A25)
Related Items (4)
The effect of the regularity of the error process on the performance of kernel regression estimators ⋮ Comments on: Dynamic relations for sparsely sampled Gaussian processes ⋮ Global smoothness estimation of a Gaussian process from general sequence designs ⋮ Estimating the order of mean-square derivatives with quadratic variations
Cites Work
- Unnamed Item
- Average case complexity of weighted approximation and integration over \(\mathbb R_{+}\)
- Uniform reconstruction of Gaussian processes
- Spatial adaption for predicting random functions
- Quadratic variations and estimation of the local Hölder index of a Gaussian process
- Accurate rates of density estimators for continuous-time processes
- Average-case analysis of numerical problems
- Optimal designs for weighted approximation and integration of stochastic processes on \([0,\infty)\)
- Multivariate integration and approximation for random fields satisfying Sacks-Ylvisaker conditions
- Optimal designs for approximating the path of a stochastic process
- On the asymptotic variance of the continuous-time kernel density estimator
- Spline approximation of random processes and design problems
- Integration of covariance kernels and stationarity
- 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
- Optimal sampling for density estimation in continuous time
- Inference for Observations of Integrated Diffusion Processes
- Large deviations in the piecewise linear approximation of Gaussian processes with stationary increments
- A Bound on Tail Probabilities for Quadratic Forms in Independent Random Variables
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