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Keywords:
random coefficient autoregressive model
random coefficient autoregressive model
Summary:
The paper concerns with a heteroscedastic random coefficient autoregressive model (RCA) of the form $X_t=b_tX_{t-1}+Y_t$. Two different procedures for estimating $\sigma _t^2=EY_t^2, \sigma _b^2=Eb_t^2$ or $\sigma _B^2=E(b_t- Eb_t)^2$, respectively, are described under the special seasonal behaviour of $\sigma _t^2$. For both types of estimators strong consistency and asymptotic normality are proved.
References:
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