Optimal Design of Experiments

Friedrich Pukelsheim

2006年4月 · Classics in Applied Mathematics 第 50 冊 · SIAM

電子書

483

頁數

符合資格

評分和評論未經驗證瞭解詳情

關於這本電子書

Optimal Design of Experiments offers a rare blend of linear algebra, convex analysis, and statistics. The optimal design for statistical experiments is first formulated as a concave matrix optimization problem. Using tools from convex analysis, the problem is solved generally for a wide class of optimality criteria such as D-, A-, or E-optimality. The book then offers a complementary approach that calls for the study of the symmetry properties of the design problem, exploiting such notions as matrix majorization and the Kiefer matrix ordering. The results are illustrated with optimal designs for polynomial fit models, Bayes designs, balanced incomplete block designs, exchangeable designs on the cube, rotatable designs on the sphere, and many other examples.

關於作者

Friedrich Pukelsheim is Chair of Stochastics and Its Applications at the Institute for Mathematics, University of Augsburg, Germany. He is a member of the Institute of Mathematical Statistics, the International Statistical Institute, and Deutsche Mathematiker-Vereinigung. He serves as editor of MetrikaInternational Journal for Theoretical and Applied Statistics.