Testing epidemic change in nearly nonstationary process with statistics based on residuals

preprint2014arXivOpen access

Abstract

We study an epidemic type change in innovations of a first order autoregressive process yn,k=φnyn,k−1+εk+an,k y_{n,k} = φ_n y_{n,k-1} + ε_{k} + a_{n,k}, where ϕnϕ_n is either a constant in (−1,1)(-1,1) or a sequence in (0,1)(0,1), converging to 1. For kk inside some unknown interval In∗=(k∗,k∗+ℓ∗]\mathbb{I}_n^\ast=(k^\ast,k^\ast+\ell^\ast], an,k=ana_{n,k}=a_n while an,k=0a_{n,k}=0 for kk outside In∗\mathbb{I}_n^\ast. When an≠0a_n\neq 0, we have an epidemic deviation from the usual (zero) mean of innovations. Since innovations are not observed, we build uniform increments statistics on residuals (ε^k)(\widehatε_k) of the process yn,ky_{n,k}. We assume that innovations (εk)(ε_k) are regularly varying with index p≥2p \ge 2 or satisfies integrability condition lim⁡t→∞tpP(∣ε1∣>t)=0\lim_{t \to \infty} t^p P(|ε_1| > t) = 0 for p>2p > 2 and Eεk2<∞Eε_k^2 < \infty for p=2p=2. We find the limit distributions of the tests under no change and prove consistency under short epidemics that is ℓ∗=O(nβ)\ell^\ast=O(n^β) for some 0<β≤1/20<β\le 1/2.

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