Robust parameter estimation for stationary processes by an exotic disparity from prediction problem

DOI10.1016/j.spl.2017.05.005zbMath1457.62271OpenAlexW2618938973MaRDI QIDQ1687202

Yan Liu

Publication date: 22 December 2017

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2017.05.005

zbMATH Keywords

asymptotic efficiencystationary processspectral densityminimum contrast estimationprediction problem

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Robustness and adaptive procedures (parametric inference) (62F35) Stationary stochastic processes (60G10) Missing data (62D10)

Related Items (2)

Unnamed Item ⋮ Robust empirical likelihood for time series

Cites Work

• Asymptotic theory of parameter estimation by a contrast function based on interpolation error
• Robust parameter estimation with a small bias against heavy contamination
• A central limit theorem for stationary processes and the parameter estimation of linear processes
• Time series: theory and methods.
• I-divergence geometry of probability distributions and minimization problems
• The integrated periodogram for stable processes
• Parameter estimation for ARMA models with infinite variance innovations
• Gaussian and non-Gaussian linear time series and random fields
• Best Approximations in L^p (d μ) and Prediction Problems of Szegö, Kolmogorov, Yaglom, and Nakazi
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