Prediction of weakly locally stationary processes by auto-regression

zbMath1404.62094arXiv1602.01942MaRDI QIDQ4962123

Françcois Roueff, Andres Sanchez-Perez

Publication date: 30 October 2018

Full work available at URL: https://arxiv.org/abs/1602.01942

zbMATH Keywords

time varying autoregressive processeslocally stationary time seriesauto-regression coefficientsminimax-rate prediction

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (3)

Autoregressive approximations to nonstationary time series with inference and applications ⋮ Asymptotic properties of conditional least-squares estimators for array time series ⋮ Predictive, finite-sample model choice for time series under stationarity and non-stationarity

Cites Work

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• Introduction to Time Series and Forecasting
• Orthogonal Samples for Estimators in Time Series
• On the fitting of multivariate autoregressions, and the approximate canonical factorization of a spectral density matrix
• Prediction, Learning, and Games

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