TY - JOUR

T1 - A bayesian decision-theoretic change-point detection for i.p.i.d. sources

AU - Suzuki, Kairi

AU - Kamatsuka, Akira

AU - Matsushima, Toshiyasu

N1 - Publisher Copyright:
© 2020 The Institute of Electronics, Information and Communication Engineers.

PY - 2020/12

Y1 - 2020/12

N2 - Change-point detection is the problem of finding points of time when a probability distribution of samples changed. There are various related problems, such as estimating the number of the changepoints and estimating magnitude of the change. Though various statistical models have been assumed in the field of change-point detection, we particularly deal with i.p.i.d. (independent-piecewise-identically-distributed) sources. In this paper, we formulate the related problems in a general manner based on statistical decision theory. Then we derive optimal estimators for the problems under the Bayes risk principle. We also propose e_cient algorithms for the change-point detection-related problems in the i.p.i.d. sources, while in general, the optimal estimations requires huge amount of calculation in Bayesian setting. Comparison of the proposed algorithm and previous methods are made through numerical examples.

AB - Change-point detection is the problem of finding points of time when a probability distribution of samples changed. There are various related problems, such as estimating the number of the changepoints and estimating magnitude of the change. Though various statistical models have been assumed in the field of change-point detection, we particularly deal with i.p.i.d. (independent-piecewise-identically-distributed) sources. In this paper, we formulate the related problems in a general manner based on statistical decision theory. Then we derive optimal estimators for the problems under the Bayes risk principle. We also propose e_cient algorithms for the change-point detection-related problems in the i.p.i.d. sources, while in general, the optimal estimations requires huge amount of calculation in Bayesian setting. Comparison of the proposed algorithm and previous methods are made through numerical examples.

KW - Bayes risk principle

KW - Change-point detection

KW - I.p.i.d. sources

KW - Statistical decision theory

UR - http://www.scopus.com/inward/record.url?scp=85098006669&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85098006669&partnerID=8YFLogxK

U2 - 10.1587/transfun.2020TAP0009

DO - 10.1587/transfun.2020TAP0009

M3 - Article

AN - SCOPUS:85098006669

VL - E103A

SP - 1393

EP - 1402

JO - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

JF - IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

SN - 0916-8508

IS - 12

ER -