Clustering Effects in Unreplicated Factorial Experiments

DOI10.1080/03610918.2012.687122zbMath1302.62177OpenAlexW2029845907MaRDI QIDQ5299938

A. Skountzou, P. Angelopoulos, Christos Koukouvinos

Publication date: 24 June 2013

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2012.687122

zbMATH Keywords

powercluster analysisfalse discovery ratetwo-level factorial designsunreplicated experiments

Mathematics Subject Classification ID

Factorial statistical designs (62K15) Diagnostics, and linear inference and regression (62J20)

Cites Work

• Estimating the Number of Clusters in a Data Set Via the Gap Statistic
• Algorithm AS 136: A K-Means Clustering Algorithm
• Quick, Easy, and Powerful Analysis of Unreplicated Factorial Designs
• Unnamed Item
• Unnamed Item

This page was built for publication: Clustering Effects in Unreplicated Factorial Experiments