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AUTOREGRESSIVE PROCESSES WITH A TIME DEPENDENT VARIANCE
Author(s) -
Tyssedal John S.,
Tjøstheim Dag
Publication year - 1982
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.1467-9892.1982.tb00343.x
Subject(s) - autoregressive model , mathematics , variance (accounting) , residual , series (stratigraphy) , star model , variance function , econometrics , setar , statistics , regression , time series , regression analysis , autoregressive integrated moving average , algorithm , paleontology , accounting , business , biology
. We study nonstationary autoregressive time series where the variance of the residual process is allowed to depend on time. In earlier publications the variance has been modelled by a step function. We look at more general classes of functions and propose two estimates of the autoregressive coefficients, both of which are consistent under weak assumptions. We also show how it is possible to obtain an estimate in practice using an iterative regression procedure.