Bayesian spectral density estimation using P-splines with quantile-based knot placement

DOI10.1007/s00180-021-01066-7zbMath1505.62278arXiv1905.01832OpenAlexW3124488199MaRDI QIDQ2667015

Patricio Maturana-Russel, Renate Meyer

Publication date: 23 November 2021

Published in: Computational Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1905.01832

zbMATH Keywords

spectral density estimationB-splinesP-splinesWhittle likelihoodBernstein-Dirichlet process prior

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Nonparametric regression and quantile regression (62G08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Bayesian inference (62F15) Inference from stochastic processes and spectral analysis (62M15)

Uses Software

• fda (R)
• GitHub
• beyondWhittle
• bsplinePsd
• BayesSpec

Cites Work

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