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: https://corec.meisei-u.ac.jp/labs/hirotsu/.
@article{bwmeta1.element.doi-10_1515_bile-2017-0001,
author = {Chihiro Hirotsu and Harukazu Tsuruta},
title = {An algorithm for a new method of change-point analysis in the independent Poisson sequence},
journal = {Biometrical Letters},
volume = {54},
year = {2017},
pages = {1-24},
language = {en},
url = {http://dml.mathdoc.fr/item/bwmeta1.element.doi-10_1515_bile-2017-0001}
}
Chihiro Hirotsu; Harukazu Tsuruta. An algorithm for a new method of change-point analysis in the independent Poisson sequence. Biometrical Letters, Tome 54 (2017) pp. 1-24. http://gdmltest.u-ga.fr/item/bwmeta1.element.doi-10_1515_bile-2017-0001/