Bayesian Spectral Modeling for Multiple Time Series

DOI10.1080/01621459.2018.1520114zbMath1428.62386OpenAlexW2890556023MaRDI QIDQ5208088

Raquel Prado, Annalisa Cadonna, Athanasios Kottas

Publication date: 15 January 2020

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01621459.2018.1520114

zbMATH Keywords

Markov chain Monte CarloGaussian mixturesWhittle likelihoodlog-periodogrammultichannel electroencephalography

Mathematics Subject Classification ID

Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Bayesian inference (62F15)

Related Items (4)

AdaptSPEC-X: Covariate-Dependent Spectral Modeling of Multiple Nonstationary Time Series ⋮ A nonparametric Bayesian model for estimating spectral densities of resting‐state EEG twin data ⋮ Nearest-neighbor mixture models for non-Gaussian spatial processes ⋮ Efficient Bayesian PARCOR approaches for dynamic modeling of multivariate time series

Uses Software

• BayesLogit
• astsa
• beyondWhittle

Cites Work

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• Bayesian Estimation of the Spectral Density of a Time Series
• Mixture Models With a Prior on the Number of Components
• Random Bernstein Polynomials
• Bayesian Inference for Logistic Models Using Pólya–Gamma Latent Variables
• Automatic estimation of multivariate spectra via smoothing splines
• The asymptotic theory of linear time-series models
• On Estimation of a Probability Density Function and Mode

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