Didier HenrionLAAS-POP, Jean Bernard LasserreLAAS-POP, TSE-R
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引用次数: 0
摘要
我们引入了 D-最优实验设计问题的一个变体,它具有更一般的信息矩阵,考虑到了设计空间 S 的表示。主要动机是,如果 S $subset$ R d 是单位球、单位盒或典型单纯形,那么对于每个维度 d 和每个度数 n,S 的平衡度量(在多能理论中)都是一个最优解。等价地,对于每个度数 n,唯一的最优解就是 S 的平衡度量的矩向量(直到度数 2n)。因此,找到最优设计就简化为找到平衡度量的立方体,S 中的原子为正权重,并且精确到度数 2n。此外,随着 n 的增加,任何由此产生的 D 原子最优度量序列都会向弱星拓扑的 S 平衡度量收敛。我们还考虑了更一般的紧凑基本代数集,而且以前开发的两步设计算法很容易适应这一新的 D-最优设计问题变体。
Approximate D-optimal design and equilibrium measure *
We introduce a variant of the D-optimal design of experiments problem with a
more general information matrix that takes into account the representation of
the design space S. The main motivation is that if S $\subset$ R d is the unit
ball, the unit box or the canonical simplex, then remarkably, for every
dimension d and every degree n, the equilibrium measure of S (in pluripotential
theory) is an optimal solution. Equivalently, for each degree n, the unique
optimal solution is the vector of moments (up to degree 2n) of the equilibrium
measure of S. Hence nding an optimal design reduces to nding a cubature for the
equilibrium measure, with atoms in S, positive weights, and exact up to degree
2n. In addition, any resulting sequence of atomic D-optimal measures converges
to the equilibrium measure of S for the weak-star topology, as n increases.
Links with Fekete sets of points are also discussed. More general compact basic
semialgebraic sets are also considered, and a previously developed two-step
design algorithm is easily adapted to this new variant of D-optimal design
problem.