Moving window approach for detecting change points in relational event data
| dc.rights.license | CC-BY-NC-ND | |
| dc.contributor.advisor | Shafiee Kamalabad, Mahdi | |
| dc.contributor.author | Rood, Sterre | |
| dc.date.accessioned | 2022-07-27T00:00:50Z | |
| dc.date.available | 2022-07-27T00:00:50Z | |
| dc.date.issued | 2022 | |
| dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/41950 | |
| dc.description.sponsorship | Utrecht University | |
| dc.language.iso | EN | |
| dc.subject | This study looks at whether a moving window approach can detect change points in relational event data. Change points are points in time where the effects of interactions change greatly. To find possible change points with a moving window approach, data from NASA's unsuccessful mission to the moon is used, Apollo 13. Additionally, the Bayes Factor is applied to statistically test whether there is evidence for some of the change points found by the moving window approach. | |
| dc.title | Moving window approach for detecting change points in relational event data | |
| dc.type.content | Master Thesis | |
| dc.rights.accessrights | Open Access | |
| dc.subject.courseuu | Applied Data Science | |
| dc.thesis.id | 6792 |
