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A GENERALIZED LEAST‐SQUARES APPROACH FOR ESTIMATION OF AUTOREGRESSIVE MOVING‐AVERAGE MODELS
Author(s) -
Koreisha Sergio,
Pukkila Tarmo
Publication year - 1990
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/j.1467-9892.1990.tb00047.x
Subject(s) - mathematics , autoregressive model , star model , autoregressive–moving average model , least squares function approximation , setar , statistics , generalized least squares , maximum likelihood , estimation , autoregressive integrated moving average , econometrics , time series , engineering , systems engineering , estimator
. In this paper we present a generalized least‐squares approach for estimating autoregressive moving‐average (ARMA) models. Simulation results based on different model structures with varying numbers of observations are used to contrast the performance of our procedure with that of maximum likelihood estimates. Existing software packages can be utilized to derive these estimates.