File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1109/WSC.2017.8247946
- Scopus: eid_2-s2.0-85044541872
- Find via
Supplementary
-
Citations:
- Scopus: 0
- Appears in Collections:
Conference Paper: Ranking and selection with covariates
Title | Ranking and selection with covariates |
---|---|
Authors | |
Issue Date | 2018 |
Publisher | IEEE. |
Citation | 2017 Winter Simulation Conference (WSC 2017), Las Vegas, NV, 3-6 December 2017. In Proceedings - Winter Simulation Conference, 2018, p. 2137-2148 How to Cite? |
Abstract | © 2017 IEEE. We consider a new ranking and selection problem in which the performance of each alternative depends on some observable random covariates. The best alternative is thus not constant but depends on the values of the covariates. Assuming a linear model that relates the mean performance of an alternative and the covariates, we design selection procedures producing policies that represent the best alternative as a function in the covariates. We prove that the selection procedures can provide certain statistical guarantee, which is defined via a nontrivial generalization of the concept of probability of correct selection that is widely used in the conventional ranking and selection setting. |
Persistent Identifier | http://hdl.handle.net/10722/271494 |
ISSN | 2023 SCImago Journal Rankings: 0.272 |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Shen, Haihui | - |
dc.contributor.author | Hong, L. Jeff | - |
dc.contributor.author | Zhang, Xiaowei | - |
dc.date.accessioned | 2019-07-02T07:16:14Z | - |
dc.date.available | 2019-07-02T07:16:14Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | 2017 Winter Simulation Conference (WSC 2017), Las Vegas, NV, 3-6 December 2017. In Proceedings - Winter Simulation Conference, 2018, p. 2137-2148 | - |
dc.identifier.issn | 0891-7736 | - |
dc.identifier.uri | http://hdl.handle.net/10722/271494 | - |
dc.description.abstract | © 2017 IEEE. We consider a new ranking and selection problem in which the performance of each alternative depends on some observable random covariates. The best alternative is thus not constant but depends on the values of the covariates. Assuming a linear model that relates the mean performance of an alternative and the covariates, we design selection procedures producing policies that represent the best alternative as a function in the covariates. We prove that the selection procedures can provide certain statistical guarantee, which is defined via a nontrivial generalization of the concept of probability of correct selection that is widely used in the conventional ranking and selection setting. | - |
dc.language | eng | - |
dc.publisher | IEEE. | - |
dc.relation.ispartof | Proceedings - Winter Simulation Conference | - |
dc.title | Ranking and selection with covariates | - |
dc.type | Conference_Paper | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/WSC.2017.8247946 | - |
dc.identifier.scopus | eid_2-s2.0-85044541872 | - |
dc.identifier.spage | 2137 | - |
dc.identifier.epage | 2148 | - |
dc.identifier.issnl | 0891-7736 | - |