Abstract
Quantile regression offers a more complete statistical model than mean regression and now has widespread applications. Consequently, we provide a review of this technique. We begin with an introduction to and motivation for quantile regression. We then discuss some typical application areas. Next we outline various approaches to estimation. We finish by briefly summarizing some recent research areas.
| Original language | English |
|---|---|
| Pages (from-to) | 331-350 |
| Journal | Journal of the Royal Statistical Society Series D: The Statistician |
| Volume | 52 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2003 |
| Externally published | Yes |
Bibliographical note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].Research Keywords
- Check function
- Conditional distribution
- Quantile
- Regression fitting
- Skew distribution
Policy Impact
- Cited in Policy Documents
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