Fast Bayesian inference on spectral analysis of multivariate stationary time series

DOI10.1016/j.csda.2022.107596OpenAlexW4293083745MaRDI QIDQ2101377

Raquel Prado, Zhixiong Hu

Publication date: 6 December 2022

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2022.107596

zbMATH Keywords

spectral analysismultivariate time seriesglobal-local shrinkage priorstochastic gradient variational Bayes

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• UCI-ml
• TensorFlow
• Adam
• BayesSpec

Cites Work

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• Sparsity information and regularization in the horseshoe and other shrinkage priors
• Adaptive spectral estimation for nonstationary multivariate time series
• Bayesian copula spectral analysis for stationary time series
• Bayesian nonparametric analysis of multivariate time series: a matrix gamma process approach
• Inference with normal-gamma prior distributions in regression problems
• Gaussian Variational Approximation With a Factor Covariance Structure
• Multivariate spectral analysis using Cholesky decomposition
• Bayesian Estimation of the Spectral Density of a Time Series
• AdaptSPEC: Adaptive Spectral Estimation for Nonstationary Time Series
• Adaptive Bayesian Spectral Analysis of High-Dimensional Nonstationary Time Series
• Adaptive Bayesian Time–Frequency Analysis of Multivariate Time Series
• Local Spectral Analysis via a Bayesian Mixture of Smoothing Splines
• Penalized multivariate Whittle likelihood for power spectrum estimation
• Automatic estimation of multivariate spectra via smoothing splines
• A Stochastic Approximation Method

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