Robust Bayesian Methods for Semi-parametric Models
| Metadata Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | Abebe, Asheber | |
| dc.contributor.author | Huang, Wei | |
| dc.date.accessioned | 2020-07-21T20:45:33Z | |
| dc.date.available | 2020-07-21T20:45:33Z | |
| dc.date.issued | 2020-07-21 | |
| dc.identifier.uri | http://hdl.handle.net/10415/7371 | |
| dc.description.abstract | Nonparametric rank-based approaches in many situations provide more flexible modeling speci cations and robustness when the distribution of data diff ers from the assumed distribution. This dissertation is mainly concerned with two robust Bayesian methods using the ideas of rank-based approaches and least absolute deviations estimate. | en_US |
| dc.rights | EMBARGO_NOT_AUBURN | en_US |
| dc.subject | Mathematics and Statistics | en_US |
| dc.title | Robust Bayesian Methods for Semi-parametric Models | en_US |
| dc.type | PhD Dissertation | en_US |
| dc.embargo.length | MONTHS_WITHHELD:12 | en_US |
| dc.embargo.status | EMBARGOED | en_US |
| dc.embargo.enddate | 2021-07-20 | en_US |