Bayesian analysis of change point problems for time series data
Chee Nian Lee, Hong Choon Ong · AIP conference proceedings · 2016
Alterations or sudden changes within a sequence of temporal observations always create disturbance to data analysis. The maneuver to detect this alterations or changes in any temporal data may allow researchers to identify the aberration in every block of segments. The Bayesian method proposed by Barry and Hartigan has greatly fitted the analysis of change point problems through product partition model. We study Bayesian analysis for change point problem with Markov sampling computation on British coal mine accident. The result provides accurate change point and posterior means estimation.