This volume provides a complete treatment of the optimality theory of experimental designs in linear models, covering a large range of design problems that originate in statistics. The author discusses the formulation of the design problem and applies results to real situations.
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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.
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Vendeur : Saul Field - Bookseller, Kingston, ON, Canada
Hardcover. Etat : Near Fine. Etat de la jaquette : Very Good. Wiley, 1993. Hardcover. Near Fine. Dust jacket very good. Slight wear to jacket. Text appears unread. N° de réf. du vendeur 500
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Vendeur : Book House in Dinkytown, IOBA, Minneapolis, MN, Etats-Unis
Hardcover. Etat : Good. Etat de la jaquette : No Dust Jacket. 3rd Printing. Good hardcover copy. Previous owner's name on pastedowns and front endpaper, about a dozen other pages with light markings. Binding is tight, sturdy, and square. Exterior looks quite nice. Ships same or next business day from Dinkytown in Minneapolis, Minnesota. N° de réf. du vendeur 336515
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