Testing stability in a spatial unilateral autoregressive model
classification
🧮 math.ST
stat.TH
keywords
alphastabilityvarrhoautoregressivebetacaseestimatorleast
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Least squares estimator of the stability parameter $\varrho := |\alpha| + |\beta|$ for a spatial unilateral autoregressive process $X_{k,\ell}=\alpha X_{k-1,\ell}+\beta X_{k,\ell-1}+\varepsilon_{k,\ell}$ is investigated. Asymptotic normality with a scaling factor $n^{5/4}$ is shown in the unstable case, i.e., when $\varrho = 1$, in contrast to the AR(p) model $X_k=\alpha_1 X_{k-1}+... +\alpha_p X_{k-p}+ \varepsilon_k$, where the least squares estimator of the stability parameter $\varrho :=\alpha_1 + ... + \alpha_p$ is not asymptotically normal in the unstable, i.e., in the unit root case.
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