On the prediction of multivariate arma processes with a time dependent covariance structure

DOI10.1080/03610928808829607zbMath0642.62052OpenAlexW2171132441MaRDI QIDQ3783389

M. Shelton Peiris

Publication date: 1988

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610928808829607

zbMATH Keywords

predictiontime seriesHilbert spaceregularity conditionsexamplesnonstationarymultivariate processm-variate ARMA modelone sided Green's matricesone sided moving averagesecond-order solutionstime dependent coefficient matricestime dependent covariance structuretime-dependent variance

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (4)

The modified Yule-Walker method for multidimensional infinite-variance periodic autoregressive model of order 1 ⋮ A note on the modelling and analysis of vector ARMA processes with nonstationary innovations ⋮ Measures of Cross‐Dependence for Bidimensional Periodic AR(1) Model with α‐Stable Distribution ⋮ Analysis of multivariate arma processes with non-stationary innovations

Cites Work

• Nonstationary Yule-Walker equations
• Spectral factorization of nonstationary moving average processes
• Mixed autoregressive-moving average multivariate processes with time- dependent coefficients
• AUTOREGRESSIVE PROCESSES WITH A TIME DEPENDENT VARIANCE
• Non-stationary q-dependent processes and time-varying moving-average models: invertibility properties and the forecasting problem
• Some Results on Non Stationary First Order Autoregression
• On Linear Difference Equations

This page was built for publication: On the prediction of multivariate arma processes with a time dependent covariance structure