Implementation of a Maximin Power Clustering Criterion to Select Near Replicates for Regression Lack-of-Fit Tests
本文进一步探讨了最大化最小功效聚类准则的实现方法，开发了一套流程来确定候选分组，以便在回归失拟检验中应用该准则选择近重复观测。
Abstract In earlier work, we presented a maximin power clustering criterion to partition observations into groups of near replicates. Specifically, the criterion selects near replicate clusters for use with Christensen's tests for orthogonal between and within cluster lack of fit. This article further explores implementation of this clustering criterion. In particular, a methodology is developed to determine a collection of candidate groupings to which the maximin power criterion can be applied.