Quantile regression: applications and current research areas
| dc.contributor.author | Yu, K. | |
| dc.contributor.author | Lu, Zudi | |
| dc.contributor.author | Stander, J. | |
| dc.date.accessioned | 2017-01-30T10:27:12Z | |
| dc.date.available | 2017-01-30T10:27:12Z | |
| dc.date.created | 2010-03-29T20:04:53Z | |
| dc.date.issued | 2009 | |
| dc.identifier.citation | Yu, Keming and Lu, Zudi and Stander, J. 2009. Quantile regression: applications and current research areas. Journal of the Royal Statistical Society, Series D. 52 (3): pp. 331-350. | |
| dc.identifier.uri | http://hdl.handle.net/20.500.11937/2933 | |
| dc.description.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. | |
| dc.publisher | Blackwell Publishing | |
| dc.relation.uri | http://www.jstor.org/stable/4128208 | |
| dc.subject | Skew distribution | |
| dc.subject | Conditional distribution | |
| dc.subject | Regression fitting | |
| dc.subject | Quantile | |
| dc.subject | Check function | |
| dc.title | Quantile regression: applications and current research areas | |
| dc.type | Journal Article | |
| dcterms.source.volume | 52 | |
| dcterms.source.number | 3 | |
| dcterms.source.startPage | 331 | |
| dcterms.source.endPage | 350 | |
| dcterms.source.issn | 0039-0526 | |
| dcterms.source.title | Journal of the Royal Statistical Society, Series D | |
| curtin.accessStatus | Fulltext not available | |
| curtin.faculty | School of Science and Computing | |
| curtin.faculty | Department of Mathematics and Statistics | |
| curtin.faculty | Faculty of Science and Engineering |