An efficient method for the estimation of multivariate moving averge models

DOI10.1080/03610928808829871zbMath0696.62349OpenAlexW2144280959MaRDI QIDQ3474140

Pentti Saikkonen, Ritva Luukkonen

Publication date: 1988

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

Full work available at URL: https://doi.org/10.1080/03610928808829871

zbMATH Keywords

asymptotic normalityStrong consistencylong autoregressionmultivariate moving average model

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (1)

Estimating multivariate autoregressive moving average models by fitting long autoregressions

Cites Work

• The information matrices of the parameters of multiple mixed time series
• The evaluation of certain quadratic forms occurring in autoregressive model fitting
• Computation of the exact likelihood function of multivariate moving average models
• ESTIMATION OF THE ORDER OF A MOVING AVERAGE MODEL FROM AUTOREGRESSIVE AND WINDOW ESTIMATES OF THE INVERSE CORRELATION FUNCTION
• Multivariate linear time series models
• REGRESSION, AUTOREGRESSION MODELS
• Estimation Of Paramters Of A Multivatiate Moving Average Model From Estimates Of The Inverse Autocovariance Function
• ASYMPTOTIC PROPERTIES OF SOME PRELIMINARY ESTIMATORS FOR AUTOREGRESSIVE MOVING AVERAGE TIME SERIES MODELS
• Autoregressive and window estimates of the inverse correlation function
• Modeling Multiple Times Series with Applications

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