File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Scopus: eid_2-s2.0-0042233438
- WOS: WOS:000081220100002
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: Uniform designs for mixture-amount experiments and for mixture experiments under order restrictions
Title | Uniform designs for mixture-amount experiments and for mixture experiments under order restrictions |
---|---|
Authors | |
Keywords | Discrepancy Isotonic Restriction Monte Carlo Optimization Multivariate Distribution Uniform Design |
Issue Date | 1999 |
Publisher | Science in China Press. The Journal's web site is located at http://www.scichina.com:8081/sciAe/EN/volumn/current.shtml |
Citation | Science In China, Series A: Mathematics, Physics, Astronomy, 1999, v. 42 n. 5, p. 456-470 How to Cite? |
Abstract | With order statistics of the uniform distribution on [0,1], exponential and beta distributions, a stochastic representation is obtained for the uniform distribution over various domains, where A-type domains are closely associated with reliability growth analysis, order restricted statistical inference and isotonic regression theory, V-type domains are connected with the mixture-amount experiments, and T-type domains are well related to mixture experiments. With these stochastic representations, the corresponding uniform distribution and number-theoretic nets can be generated. This approach seems to be new and is called order statistics method. Some examples on reliability growth analysis and experimental design are presented. |
Persistent Identifier | http://hdl.handle.net/10722/172404 |
ISSN | 2011 Impact Factor: 0.701 |
ISI Accession Number ID | |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Tian, G | en_US |
dc.contributor.author | Fang, K | en_US |
dc.date.accessioned | 2012-10-30T06:22:21Z | - |
dc.date.available | 2012-10-30T06:22:21Z | - |
dc.date.issued | 1999 | en_US |
dc.identifier.citation | Science In China, Series A: Mathematics, Physics, Astronomy, 1999, v. 42 n. 5, p. 456-470 | en_US |
dc.identifier.issn | 1006-9283 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/172404 | - |
dc.description.abstract | With order statistics of the uniform distribution on [0,1], exponential and beta distributions, a stochastic representation is obtained for the uniform distribution over various domains, where A-type domains are closely associated with reliability growth analysis, order restricted statistical inference and isotonic regression theory, V-type domains are connected with the mixture-amount experiments, and T-type domains are well related to mixture experiments. With these stochastic representations, the corresponding uniform distribution and number-theoretic nets can be generated. This approach seems to be new and is called order statistics method. Some examples on reliability growth analysis and experimental design are presented. | en_US |
dc.language | eng | en_US |
dc.publisher | Science in China Press. The Journal's web site is located at http://www.scichina.com:8081/sciAe/EN/volumn/current.shtml | en_US |
dc.relation.ispartof | Science in China, Series A: Mathematics, Physics, Astronomy | en_US |
dc.subject | Discrepancy | en_US |
dc.subject | Isotonic Restriction | en_US |
dc.subject | Monte Carlo Optimization | en_US |
dc.subject | Multivariate Distribution | en_US |
dc.subject | Uniform Design | en_US |
dc.title | Uniform designs for mixture-amount experiments and for mixture experiments under order restrictions | en_US |
dc.type | Article | en_US |
dc.identifier.email | Tian, G: gltian@hku.hk | en_US |
dc.identifier.authority | Tian, G=rp00789 | en_US |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.scopus | eid_2-s2.0-0042233438 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-0042233438&selection=ref&src=s&origin=recordpage | en_US |
dc.identifier.volume | 42 | en_US |
dc.identifier.issue | 5 | en_US |
dc.identifier.spage | 456 | en_US |
dc.identifier.epage | 470 | en_US |
dc.identifier.isi | WOS:000081220100002 | - |
dc.publisher.place | China | en_US |
dc.identifier.scopusauthorid | Tian, G=25621549400 | en_US |
dc.identifier.scopusauthorid | Fang, K=7102880697 | en_US |