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Asymptotic Behavior of Conditional Least Squares Estimators for Unstable Integer‐valued Autoregressive Models of Order 2
Author(s) -
Barczy Mátyás,
Ispány Márton,
Pap Gyula
Publication year - 2014
Publication title -
scandinavian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.359
H-Index - 65
eISSN - 1467-9469
pISSN - 0303-6898
DOI - 10.1111/sjos.12069
Subject(s) - mathematics , autoregressive model , estimator , star model , integer (computer science) , statistics , least squares function approximation , setar , conditional variance , stability (learning theory) , autoregressive conditional heteroskedasticity , econometrics , autoregressive integrated moving average , time series , computer science , programming language , volatility (finance) , machine learning
In this paper, the asymptotic behavior of the conditional least squares estimators of the autoregressive parameters, of the mean of the innovations, and of the stability parameter for unstable integer‐valued autoregressive processes of order 2 is described. The limit distributions and the scaling factors are different according to the following three cases: (i) decomposable, (ii) indecomposable but not positively regular, and (iii) positively regular models.