Comparative performance analysis of the Cumulative Sum chart and the Shiryaev‐Roberts procedure for detecting changes in autocorrelated data

@article{Polunchenko2018ComparativePA,
  title={Comparative performance analysis of the Cumulative Sum chart and the Shiryaev‐Roberts procedure for detecting changes in autocorrelated data},
  author={Aleksey S. Polunchenko and Vasanthan Raghavan},
  journal={Applied Stochastic Models in Business and Industry},
  year={2018}
}
We consider the problem of quickest change-point detection where the observations form a first-order autoregressive (AR) process driven by temporally independent standard Gaussian noise. Subject to possible change are both the drift of the AR(1) process ($\mu$) as well as its correlation coefficient ($\lambda$), both known. The change is abrupt and persistent, and is of known magnitude, with $\vert\lambda\vert<1$ throughout. For this scenario, we carry out a comparative performance analysis of… 

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