Bayesian nonparametric analysis of multivariate time series: a matrix gamma process approach

DOI10.1016/j.jmva.2019.104560zbMath1475.62156arXiv1811.10292OpenAlexW2981316495WikidataQ123417515 ScholiaQ123417515MaRDI QIDQ2293389

Alexander Meier, Claudia Kirch, Renate Meyer

Publication date: 5 February 2020

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1811.10292

zbMATH Keywords

Bayesian nonparametricsspectral densitycompletely random measuresstationary multivariate time series

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Gaussian processes (60G15) Asymptotic properties of nonparametric inference (62G20) Inference from stochastic processes and spectral analysis (62M15)

Related Items (4)

Bayesian spectral density estimation using P-splines with quantile-based knot placement ⋮ Posterior consistency for the spectral density of non‐Gaussian stationary time series ⋮ On quasi-infinitely divisible random measures ⋮ Fast Bayesian inference on spectral analysis of multivariate stationary time series

Uses Software

• astsa
• beyondWhittle

Cites Work

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