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Asymptotic inference for AR(1) processes with (nonnormal) stable errors

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Abstract

This is the first of several papers in which we consider problems related to the asymptotic distribution of the least squares estimate of the parameter γ in theAR(1) model

$$X_k = \gamma X_{k - 1} + \varepsilon _k , k = 1,...,n,$$

where εk are independent identically distributed (i.i.d.) random variables in the domain of attraction of a stable law. In §1 we give a summary in the case εk is in the domain of attraction of the normal distribution. In §2 we consider errors in the domain of attraction of a (nonnormal) stable distribution. In §3 we prove a result in the case of the completely asymmetric stable distribution with α=β=1.

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Proceedings of the XVII Seminar on Stability Problems for Stochastic Models, Kazan, Russia, 1995, Part II.

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Mijnheer, J. Asymptotic inference for AR(1) processes with (nonnormal) stable errors. J Math Sci 83, 401–406 (1997). https://doi.org/10.1007/BF02400925

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