Bayesian copula spectral analysis for stationary time series

DOI10.1016/j.csda.2018.10.001OpenAlexW2896831828MaRDI QIDQ1727902

Shibin Zhang

Publication date: 21 February 2019

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

Full work available at URL: https://doi.org/10.1016/j.csda.2018.10.001

zbMATH Keywords

copulatime seriesspectral analysisWhittle likelihoodtime reversibilityHamiltonian Monte Carlo

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Bayesian inference (62F15) Inference from stochastic processes and spectral analysis (62M15)

Related Items (5)

A semi-parametric estimation method for the quantile spectrum with an application to earthquake classification using convolutional neural network ⋮ Nonparametric Bayesian inference for the spectral density based on irregularly spaced data ⋮ Automatic estimation of spatial spectra via smoothing splines ⋮ A copula spectral test for pairwise time reversibility ⋮ Fast Bayesian inference on spectral analysis of multivariate stationary time series

Uses Software

• astsa
• quantspec
• BayesSpec

Cites Work

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• Quantile spectral processes: asymptotic analysis and inference
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• Bayesian mixture of splines for spatially adaptive nonparametric regression
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• Quantile Spectral Analysis for Locally Stationary Time Series
• AdaptSPEC: Adaptive Spectral Estimation for Nonstationary Time Series
• Quantile Periodograms
• Empirical likelihood methods for discretely observed Gaussian moving averages
• Local Spectral Analysis via a Bayesian Mixture of Smoothing Splines
• Penalized multivariate Whittle likelihood for power spectrum estimation
• Statistical Analysis Based on a Certain Multivariate Complex Gaussian Distribution (An Introduction)
• Quantile Autoregression

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