Bayesian changepoints detection for the power law process with binary segmentation procedures
- Title
- Bayesian changepoints detection for the power law process with binary segmentation procedures
- Author
- 김성욱
- Keywords
- Binary segmentation; Changepoint; Model selection; Intrinsic prior; Power Law process
- Issue Date
- 2005-08
- Publisher
- 한국통계학회
- Citation
- CSAM(Communications for Statistical Applications and Methods), v. 12, No. 2, Page. 483-496
- Abstract
- We consider the power law process which is assumed to have multiple changepoints.
We propose a binary segmentation procedure for locating all existing changepoints.
We select one model between the no-changepoints model and the single changepoint
model by the Bayes factor. We repeat this procedure until no more changepoints are
found. Then we carry out a multiple test based on the Bayes factor through the
intrinsic priors of Berger and Pericchi (1996) to investigate the system behaviour
of failure times. We demonstrate our procedure with a real dataset and some
simulated datasets.
- URI
- http://kiss.kstudy.com/thesis/thesis-view.asp?key=2462173https://repository.hanyang.ac.kr/handle/20.500.11754/111403
- ISSN
- 2287-7843
- Appears in Collections:
- COLLEGE OF SCIENCE AND CONVERGENCE TECHNOLOGY[E](과학기술융합대학) > APPLIED MATHEMATICS(응용수학과) > Articles
- Files in This Item:
There are no files associated with this item.
- Export
- RIS (EndNote)
- XLS (Excel)
- XML