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ROBUST ESTIMATION AND HYPOTHESIS TESTS FOR FIRST‐ORDER THRESHOLD AUTOREGRESSIVE MODELS
Author(s) -
Kulkarni P.M.
Publication year - 1992
Publication title -
australian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 0004-9581
DOI - 10.1111/j.1467-842x.1992.tb01047.x
Subject(s) - autoregressive model , wald test , estimator , asymptotic distribution , mathematics , star model , statistics , threshold model , statistical hypothesis testing , econometrics , null hypothesis , score test , setar , normality , robust statistics , alternative hypothesis , autoregressive integrated moving average , time series
Summary Results of Petrucelli & Woolford (1984) for a first‐order threshold autoregressive model are considered from a robust point of view. Robust estimators of the threshold parameters of the model are obtained and their asymptotic normality is proved. Testing the equality of the threshold parameters is considered using the robust analogues of Wald and score test statistics. Limiting distributions of these statistics are given under both null and alternative hypotheses.