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

Chihiro Hirotsu, and Harukazu Tsuruta. "An algorithm for a new method of change-point analysis in the independent Poisson sequence." Biometrical Letters 54.1 (2017): 1-24. <http://eudml.org/doc/288448>.

@article{ChihiroHirotsu2017,
abstract = {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/.},
author = {Chihiro Hirotsu, Harukazu Tsuruta},
journal = {Biometrical Letters},
keywords = {Convexity hypothesis; Markov property; Monotone hypothesis; Slope change point model; Step change point model},
language = {eng},
number = {1},
pages = {1-24},
title = {An algorithm for a new method of change-point analysis in the independent Poisson sequence},
url = {http://eudml.org/doc/288448},
volume = {54},
year = {2017},
}

TY - JOUR
AU - Chihiro Hirotsu
AU - Harukazu Tsuruta
TI - An algorithm for a new method of change-point analysis in the independent Poisson sequence
JO - Biometrical Letters
PY - 2017
VL - 54
IS - 1
SP - 1
EP - 24
AB - 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/.
LA - eng
KW - Convexity hypothesis; Markov property; Monotone hypothesis; Slope change point model; Step change point model
UR - http://eudml.org/doc/288448
ER -