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Optimal Weights for Experimental Designs on Linearly Independent Support Points
Friedrich Pukelsheim and Ben Torsney
The Annals of Statistics
Vol. 19, No. 3 (Sep., 1991), pp. 1614-1625
Published by: Institute of Mathematical Statistics
Stable URL: http://www.jstor.org/stable/2241966
Page Count: 12
You can always find the topics here!Topics: Matrices, Linear regression, Experiment design, Statism, Mathematical theorems, Mathematical problems, Design optimization, Mathematical monotonicity, Linear models, Differential calculus
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An explicit formula is derived to compute the A-optimal design weights on linearly independent regression vectors, for the mean parameters in a linear model with homoscedastic variances. The formula emerges as a special case of a general result which holds for a wide class of optimality criteria. There are close links to iterative algorithms for computing optimal weights.
The Annals of Statistics © 1991 Institute of Mathematical Statistics