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”...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Statistical papers (Berlin, Germany) Jg. 57; H. 4; S. 893 - 910
Hauptverfasser:	Burclova, Katarina, Pazman, Andrej
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2016 Springer Nature B.V
Schlagworte:	Approximation Computation Design of experiments Design optimization Economic Theory/Quantitative Economics/Mathematical Methods Economics Eigenvalues Finance Inequality Insurance Linear programming Management Mathematical functions Mathematical models Mathematics and Statistics Operations Research/Decision Theory Optimality criteria Optimization Probability Theory and Stochastic Processes Regression Regression analysis Regular Article Statistics Statistics for Business Studies Texts Regression models 62J05 Concave maximization 62K05 Relaxation method Criterion-robust design Optimality criteria
ISSN:	0932-5026, 1613-9798
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!