Blocked Two-Level Regular Designs with Individual Aliased Effect Number Pattern
Min Han, Shengli Zhao, Tao Sun
TL;DR
This paper introduces a new pattern for blocked experimental designs and compares it with existing criteria.
Contribution
The novel BI-AENP pattern and its algorithm for regular blocked designs are introduced.
Findings
A new pattern called BI-AENP is proposed for regular blocked designs.
An algorithm is developed to compute the BI-AENP.
A catalogue of designs with 16-, 32-, and 64-run BI-AENP is provided.
Abstract
This paper proposes a blocked individual aliased effect number pattern (BI-AENP) for regular blocked designs and establishes its relationships with the core patterns of several existing optimality criteria. We develop an algorithm to compute the BI-AENP. A catalogue of 16-, 32-, and 64-run BI-AENP 2n−k:2r designs is presented, together with comparisons with the minimum aberration and clear effects criteria.
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Taxonomy
TopicsOptimal Experimental Design Methods · graph theory and CDMA systems · Statistical Methods in Clinical Trials