Two-level factorial designs with extreme numbers of level changes

DOI10.1214/aos/1024691252zbMath0929.62084OpenAlexW2041449430MaRDI QIDQ1807124

Yanyan Li

Publication date: 9 November 1999

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/aos/1024691252

zbMATH Keywords

orthogonal arraysresolutionregular fractional factorial designsrun orders

Mathematics Subject Classification ID

Orthogonal arrays, Latin squares, Room squares (05B15) Factorial statistical designs (62K15)

Related Items (15)

Experimentation order in factorial designs: new findings ⋮ Efficient factorial experiments when the data are spatially correlated ⋮ MULTI-LEVEL FACTORIAL DESIGNS WITH MINIMUM NUMBERS OF LEVEL CHANGES ⋮ Experimentation order with good properties for 2^kfactorial designs ⋮ Minimum Aberration Two-Level Fractional Factorial Split-Plot Designs with Hard to Change Factors ⋮ Definitive screening designs with extreme numbers of level changes ⋮ Minimum cost trend-free \(2^{n -(n - k)}\) fractional factorial designs of resolution IV derivable from the normalized Sylvester-Hadamard matrices ⋮ Alternative optimal foldover plans for regular fractional factorial split-plot designs ⋮ Minimum cost linear trend-free 12-run fractional factorial designs ⋮ Run orders for efficient two level experimental plans with minimum factor level changes robust to time trends ⋮ Minimum Cost Linear Trend Free 2^n-(n-k)Designs of Resolution IV ⋮ Structured orthogonal families of one and two strata prime basis factorial models ⋮ Minimum cost linear trend free fractional factorial designs ⋮ Some results on multi-level factorial designs with dependent obervations ⋮ On the generation of factorial designs with minimum level changes

Cites Work

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• Trend robust two-level factorial designs
• The Construction of Trend-Free Run Orders of Two-Level Factorial Designs
• Minimum Aberration 2 k-p Designs
• Designing Experiments When Run Order Is Important
• AN ALGORITHM FOR THE DESIGN OF 2? FACTORIAL EXPERIMENTS ON CONTINUOUS PROCESSES

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