Robust parameter estimation and pivotal inference under heterogeneous and nonstationary processes
Robust parameter estimation and pivotal inference is crucial for credible statistical conclusions. This thesis addresses these issues in three contexts: long-memory parameter estimation robust to low frequency nonstationary contamination, long-memory properties of financial time series, and inferenc...
| Main Author: | |
|---|---|
| Language: | en_US |
| Published: |
2016
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/2144/14075 |