Inference after model selection.
- Resource Type
- Theses
- Authors
- Dong, Yingwen
- Source
- Dissertation Abstracts International; Dissertation Abstract International; 68-08B.
- Subject
- Statistics
- Language
- English
Summary: A simple example of linear regression is shown to highlight the difficulty of deriving the statistical properties of estimators after model selection, as well as the effects of the uncertainty of model selection. A data perturbation approach is proposed to obtain an estimate of model selection probability. The performance of this method and its application in hypothesis testing are demonstrated through simulation. We also proposed a method to construct a confidence interval through data perturbation. The performance, as compared to the common alternatives, is examined through simulation in various situations.