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- W2949497316 abstract "We improve the inequality used in Pronzato [2003. Removing non-optimal support points in D-optimum design algorithms. Statist. Probab. Lett. 63, 223-228] to remove points from the design space during the search for a $D$-optimum design. Let $xi$ be any design on a compact space $mathcal{X} subset mathbb{R}^m$ with a nonsingular information matrix, and let $m+epsilon$ be the maximum of the variance function $d(xi,mathbf{x})$ over all $mathbf{x} in mathcal{X}$. We prove that any support point $mathbf{x}_{*}$ of a $D$-optimum design on $mathcal{X}$ must satisfy the inequality $d(xi,mathbf{x}_{*}) geq m(1+epsilon/2-sqrt{epsilon(4+epsilon-4/m)}/2)$. We show that this new lower bound on $d(xi,mathbf{x}_{*})$ is, in a sense, the best possible, and how it can be used to accelerate algorithms for $D$-optimum design." @default.
- W2949497316 created "2019-06-27" @default.
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- W2949497316 date "2007-01-01" @default.
- W2949497316 modified "2023-09-27" @default.
- W2949497316 title "Improvements on removing non-optimal support points in D-optimum design algorithms" @default.
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