ALGORITHMS FOR ESTIMATION OF POSSIBLY NONSTATIONARY VECTOR TIME SERIES

DOI10.1111/j.1467-9892.1992.tb00101.xzbMath0850.62669OpenAlexW2088111833MaRDI QIDQ4012956

Guofu Zhou

Publication date: 27 September 1992

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1467-9892.1992.tb00101.x

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

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Efficient Bayesian PARCOR approaches for dynamic modeling of multivariate time series

Cites Work

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• Covariance characterization by partial autocorrelation matrices
• Time series: theory and methods
• Antithetic acceleration of Monte Carlo integration in Bayesian inference
• Computation of the exact likelihood function of multivariate moving average models
• Some efficient computational procedures for high order ARMA models
• Algorithm AS 197: A Fast Algorithm for the Exact Likelihood of Autoregressive-Moving Average Models
• Measures of Conditional Linear Dependence and Feedback Between Time Series
• Computing the likelihood and its dierivatives for a gaussian ARMA model
• Likelihood Function of Stationary Multiple Autoregressive Moving Average Models
• Spurious Periodicity in Inappropriately Detrended Time Series
• Modeling Multiple Times Series with Applications
• Maximum Likelihood Estimation of Stochastic Linear Difference Equations with Autoregressive Moving Average Errors
• An algorithm for the exact likelihood of a mixed autoregressive-moving average process
• Time Series Regression with a Unit Root
• On the fitting of multivariate autoregressions, and the approximate canonical factorization of a spectral density matrix