A note on obtaining the theoretical autocovariances of an ARMA process

DOI10.1080/00949658208810594zbMath0505.62080OpenAlexW2083378578MaRDI QIDQ4742199

Robert Kohn, Craig F. Ansley

Publication date: 1982

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949658208810594

zbMATH Keywords

theoretical autocovariancesvector ARMAlikelihood of stationary ARMA processstable fixed point iteration

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Iterative numerical methods for linear systems (65F10) Probabilistic methods, stochastic differential equations (65C99)

Related Items

The exact Gaussian likelihood estimation of time-dependent VARMA models ⋮ A note on reparameterizing a vector autoregressive moving average model to enforce stationarity ⋮ FISHER'S INFORMATION MATRIX FOR SEASONAL AUTOREGRESSIVE-MOVING AVERAGE MODELS ⋮ Exact maximum likelihood estimation of structured or unit root multivariate time series models ⋮ A note on the derivation of theoretical autocovariances for ARMA models ⋮ ESTIMATION OF MULTIVARIATE TIME SERIES ⋮ Analytic derivatives for estimation of linear dynamic models ⋮ Derivation of the unconditional state-covariance matrix for exact maximum-likelihood estimation of ARMA models

Uses Software

• AS 154

Cites Work

• Unnamed Item
• The evaluation of exact maximum likelihood estimates for varma models
• Computation of the theoretical autocovariance function for a vector arma process
• Algorithm AS 154: An Algorithm for Exact Maximum Likelihood Estimation of Autoregressive-Moving Average Models by Means of Kalman Filtering
• An algorithm for the exact likelihood of a mixed autoregressive-moving average process