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arXiv · 2101.01590

Mixing convergence of LSE for supercritical AR(2) processes with Gaussian innovations using random scaling

Matyas Barczy·Fanni Nedényi·Gyula Pap
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Abstract

We prove mixing convergence of the least squares estimator of autoregressive parameters for supercritical autoregressive processes of order 2 with Gaussian innovations having real characteristic roots with different absolute values. We use an appropriate random scaling such that the limit distribution is a two-dimensional normal distribution concentrated on a one-dimensional ray determined by the characteristic root having the larger absolute value.

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Matyas Barczy, Fanni Nedényi, Gyula Pap. 2021-01-05. Mixing convergence of LSE for supercritical AR(2) processes with Gaussian innovations using random scaling. https://arxiv.org/abs/2101.01590

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