Bayesian non-parametric signal extraction for Gaussian time series

DOI10.1016/j.jeconom.2010.03.041zbMath1431.62435OpenAlexW2045398387MaRDI QIDQ736535

Christian Macaro

Publication date: 4 August 2016

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jeconom.2010.03.041

zbMATH Keywords

spectral representationunobserved componentsidentification conditions

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Bayesian inference (62F15) Inference from stochastic processes and spectral analysis (62M15)

Related Items (2)

Spectral decompositions of multiple time series: a Bayesian non-parametric approach ⋮ Bayesian nonparametric spectral density estimation using B-spline priors

Uses Software

• R
• Amelia
• Mcmcpack
• ismev

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Forecasting realized volatility using a long-memory stochastic volatility model: estimation, prediction and seasonal adjustment
• Trends and cycles in economic time series: a Bayesian approach
• Bayesian forecasting and dynamic models.
• Bayesian Inference on Periodicities and Component Spectral Structure in Time Series
• Temporal Aggregation of Garch Processes
• Bayesian density estimation using bernstein polynomials
• Miscellanea. Time series decomposition
• A simple and efficient simulation smoother for state space time series analysis
• Bayesian Estimation of the Spectral Density of a Time Series
• Econometric Analysis of Realized Volatility and its Use in Estimating Stochastic Volatility Models
• Time‐varying autoregressions with model order uncertainty
• Priors and Component Structures in Autoregressive Time Series Models
• Time Series Analysis of Non-Gaussian Observations Based on State Space Models from Both Classical and Bayesian Perspectives
• Random Bernstein Polynomials
• Modeling and Forecasting Realized Volatility
• An Introduction to Polyspectra
• A Monte Carlo Comparison of the Regression Method and the Spectral Methods of Prediction
• An introduction to statistical modeling of extreme values

This page was built for publication: Bayesian non-parametric signal extraction for Gaussian time series