English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Consider the problem of constructing an experimental design that is optimalfor a given statistical model with respect to a chosen criterion. To addressthis problem, the literature typically provides a single solution; sometimes,however, there exists a rich set of optimal designs. The knowledge of this setallows the experimenter to select an optimal design based on its secondaryproperties.  In this paper, we show that the set of all optimal approximate designs oftencorresponds to a polytope. The polytope can be fully represented by the set ofits vertices, which we call vertex optimal designs. We prove that these optimaldesigns possess unique characteristics, such as small supports, and suggesttheir potential applications. We also demonstrate that for a variety of models,the vertex optimal designs can be computed using rational arithmetic withperfect accuracy. Consequently, we enumerate all vertex optimal designs forseveral standard multifactor regression models.

The Polytope of Optimal Approximate Designs: Extending the Selection of Efficient Experiments