Efficient Bayesian PARCOR approaches for dynamic modeling of multivariate time series

DOI10.1111/jtsa.12534zbMath1454.62275arXiv1907.08733OpenAlexW3027701452MaRDI QIDQ5135321

Raquel Prado, Wenjie Zhao

Publication date: 20 November 2020

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1907.08733

zbMATH Keywords

multivariate time seriestime-varying vector autoregressionsBayesian dynamic linear modelstime-varying partial autocorrelations

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Applications of statistics to environmental and related topics (62P12) Inference from stochastic processes and spectral analysis (62M15)

Related Items (1)

Bayesian circular lattice filters for computationally efficient estimation of multivariate time-varying autoregressive models

Cites Work

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• Bayesian lattice filters for time-varying autoregression and time-frequency analysis
• Bayesian forecasting and dynamic models.
• Time series: theory and methods.
• Dynamics \& sparsity in latent threshold factor models: a study in multivariate EEG signal processing
• Partial directed coherence: a new concept in neural structure determination
• Time Series Analysis and Its Applications
• Conditional adaptive Bayesian spectral analysis of nonstationary biomedical time series
• ALGORITHMS FOR ESTIMATION OF POSSIBLY NONSTATIONARY VECTOR TIME SERIES
• Automatic Statistical Analysis of Bivariate Nonstationary Time Series
• Bayesian Spectral Modeling for Multiple Time Series
• Adaptive Bayesian Time–Frequency Analysis of Multivariate Time Series

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