A spectral approach to estimate the autocovariance function
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Publication:2156825
DOI10.1016/j.jspi.2022.05.005OpenAlexW4281623055WikidataQ113869770 ScholiaQ113869770MaRDI QIDQ2156825
Valdério Anselmo Reisen, Pascal Bondon, Céline Lévy-Leduc
Publication date: 20 July 2022
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jspi.2022.05.005
Cites Work
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- Highly Robust Estimation of the Autocovariance Function
- Fast and exact synthesis of stationary multivariate Gaussian time series using circulant embedding
- \(M\)-estimation of linear models with dependent errors
- Central limit theorems for non-linear functionals of Gaussian fields
- Time series: theory and methods.
- An \(M\)-estimator for the long-memory parameter
- A unified view of multitaper multivariate spectral estimation
- Fast and Exact Simulation of Complex-Valued Stationary Gaussian Processes Through Embedding Circulant Matrix
- Laplace Periodogram for Time Series Analysis
- M-periodogram for the analysis of long-range-dependent time series
- A Nonlinear Method for Robust Spectral Analysis
- Robust estimation of the scale and of the autocovariance function of Gaussian short- and long-range dependent processes
- Spectral Analysis for Univariate Time Series
- Robust Statistics
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