The Asymptotics of Optimal Designs for Polynomial Regression
T. Bloom, L. Bos, N. Levenberg
TL;DR
This paper analyzes the asymptotic behavior of optimal experimental designs for polynomial regression on compact spaces, providing insights into their long-term properties and efficiency.
Contribution
It offers the first detailed asymptotic analysis of D- and G-optimal designs for polynomial regression on complex and real compact spaces.
Findings
Asymptotic formulas for D- and G-optimal designs
Insights into design efficiency in large-sample limits
Extension to complex design spaces
Abstract
We give the asymptotics for D-optimal (equivalently G-optimal) designs on a compact (possibly complex) design space.
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Taxonomy
TopicsPoint processes and geometric inequalities · Bayesian Methods and Mixture Models · Mathematical functions and polynomials