Leisen, Fabrizio, Hinoveanu, Laurentiu, Villa, Cristiano (2019) Bayesian Loss-based Approach to Change Point Analysis. Computational Statistics and Data Analysis, 129 . pp. 61-78. ISSN 0167-9473. (doi:10.1016/j.csda.2018.08.008) (KAR id:69002)
PDF
Author's Accepted Manuscript
Language: English
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
|
|
Download this file (PDF/705kB) |
|
Request a format suitable for use with assistive technology e.g. a screenreader | |
Official URL: https://doi.org/10.1016/j.csda.2018.08.008 |
Abstract
A loss-based approach to change point analysis is proposed. In particular, the problem is looked from two perspectives. The first focuses on the definition of a prior when the number of change points is known a priori. The second contribution aims to estimate the number of change points by using a loss-based approach recently introduced in the literature. The latter considers change point estimation as a model selection exercise. The performance of the proposed approach it is shown on simulated data and real data sets.
Item Type: | Article |
---|---|
DOI/Identification number: | 10.1016/j.csda.2018.08.008 |
Uncontrolled keywords: | Change pointDiscrete parameter spaceLoss-based priorModel selection |
Subjects: |
H Social Sciences > HA Statistics Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science |
Depositing User: | Fabrizio Leisen |
Date Deposited: | 08 Sep 2018 14:42 UTC |
Last Modified: | 05 Nov 2024 12:30 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/69002 (The current URI for this page, for reference purposes) |
- Link to SensusAccess
- Export to:
- RefWorks
- EPrints3 XML
- BibTeX
- CSV
- Depositors only (login required):