An algorithm for a new method of change-point analysis in the independent Poisson sequence

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Step change-point and slope change-point models in the independent Poisson sequence are developed based on accumulated and doubly-accumulated statistics. The method for the step change-point model developed in Section 2 is an alternative to the likelihood ratio test of Worsley (1986) and the algorithm for p-value calculation based on the first-order Markov property is the same as that given there. Different algorithms for the non-null distribution and inference on the change-point itself are, however, newly developed and a Pascal program is given in the Appendix. These methods are extended to the slope change-point model in Section 3. The approach is essentially the same as that of Section 2 but the algorithm is now based on the second-order Markov property and becomes a little more complicated. The Pascal program related to the slope change-point model is supported on the website, URL:

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  • Hirotsu C. (1982). Use of cumulative efficient scores for testing ordered alternatives in discrete models. Biometrika 69:567-577.

  • Hirotsu C. (2013). Theory and its application of the cumulative two-way cumulative and doubly cumulative sum statistics. Jap. J. Appl. Statist. 42:121-143. (In Japanese)

  • Hirotsu C. and Marumo K. (2002). Change point analysis as a method for isotonic inference. Scand. J. Statist. 29:125-138.

  • Hirotsu C. Yamamoto S. and Tsuruta H. (2016). A unifying approach to the shape and change-point hypotheses in the discrete univariate exponential family. Comput. Statist. Data Anal. 97:33-46.

  • Worsley K. J. (1986): Confidence regions and tests for a change-point in a sequence of exponential family of random variables. Biometrika 73:91-104.

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