On the estimation of periodic signals in the diffusion process using a high-frequency scheme
From MaRDI portal
Publication:6123186
DOI10.1515/mcma-2023-2020OpenAlexW4388564138MaRDI QIDQ6123186
Publication date: 4 March 2024
Published in: Monte Carlo Methods and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1515/mcma-2023-2020
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic behavior of solutions to PDEs (35B40) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)
Cites Work
- Statistical signal processing. Frequency estimation.
- Introduction to data science. A Python approach to concepts, techniques and applications. With contributions from Jordi Vitrià, Eloi Puertas Petia Radeva, Oriol Pujol, Sergio Escalera, Francesc Dantí and Lluís Garrido
- Asymptotic theory of least squares estimator of a particular nonlinear regression model
- On the estimation of the diffusion coefficient for multi-dimensional diffusion processes
- Parameter least-squares estimation for time-inhomogeneous Ornstein-Uhlenbeck process
- Asymptotic properties of the high-order Yule-Walker estimates of sinusoidal frequencies
- Maximum likelihood localization of multiple sources by alternating projection
- On the estimation of a harmonic component in a time series with stationary independent residuals
- The simultaneous estimation of a time series harmonic components and covariance structure
This page was built for publication: On the estimation of periodic signals in the diffusion process using a high-frequency scheme