Epidemic change-point detection in general causal time series

Mamadou Lamine Diop and William Kengne

Statistics & Probability Letters, 2022, vol. 184, issue C

Abstract: We consider an epidemic change-point detection in a large class of causal time series models, including among other processes, AR(∞), ARCH(∞), TARCH(∞), ARMA-GARCH. A test statistic based on the Gaussian quasi-maximum likelihood estimator of the parameter is proposed. It is shown that, under the null hypothesis of no change, the test statistic converges to a distribution obtained from a difference of two Brownian bridge and diverges to infinity under the epidemic alternative. Numerical results for simulation and real data example are provided.

Keywords: Causal processes; Epidemic change-point; Semi-parametric statistic; Quasi-maximum likelihood estimator (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1016/j.spl.2022.109416

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