Optimal design of experiments via linear programming
We investigate the possibility of extending some results of Pázman and Pronzato (Ann Stat 42(4):1426–1451, 2014 ) to a larger set of optimality criteria. Namely, the problems of computing D -, A -, and E k -optimal designs in a linear regression model are reformulated here as “infinite-dimensional”...
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| Vydáno v: | Statistical papers (Berlin, Germany) Ročník 57; číslo 4; s. 893 - 910 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.12.2016
Springer Nature B.V |
| Témata: | |
| ISSN: | 0932-5026, 1613-9798 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | We investigate the possibility of extending some results of Pázman and Pronzato (Ann Stat 42(4):1426–1451,
2014
) to a larger set of optimality criteria. Namely, the problems of computing
D
-,
A
-, and
E
k
-optimal designs in a linear regression model are reformulated here as “infinite-dimensional” linear programming problems. The same approach is applied to combination of these optimality criteria and to the “criterion robust” problem of Harman (Metrika 60:137–153,
2004
). Approximate optimum designs can then be computed by a relaxation method (Shimizu and Aiyoshi in IEEE Trans Autom Control 25(1):62–66,
1980
), and this is illustrated on various examples. |
|---|---|
| Bibliografie: | SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 0932-5026 1613-9798 |
| DOI: | 10.1007/s00362-016-0782-7 |