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Three replicated runs lasted 9 d each, with 7 d for adaptation period and 2 d for data collection.
Fractional factorial designs with partially replicated runs are desirable, since they not only save experimental cost and but also estimate the experimental error variance.
Theoretical results and examples show that the constructed designs are more flexible than most of the existing results in terms of the replicated runs.
In this paper, a simple technique called as quarter foldover, which can construct two-level factorial designs with flexible partially replicated runs, is firstly proposed.
For model-based cluster analysis, Structure 2.3.3 (Pritchard et al. [2000]) was used using 10 replicated runs each for populations K = 1-10, with run length = 500,000 iterations, followed by 100,000 burn-in length.
For initial designs of 12, 16, 20 and 24 runs with s factors, where 3≤s≤6, a catalog of optimal plans to construct some designs with highest resolution and flexible partially replicated runs is also tabulated for practice.
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There comes, as I wrote before, a time when the ease of replicating runs out.
Bootstrap values (1000 replicate runs, %) >70%% are listed.
Branch support was calculated by bootstrap with 1000 replicate runs.
Bootstrap values (1000 replicate runs, shown as %) greater than 70% are listed.
Six typical volatile peaks were recorded every 4 min for each of the three replicate runs.
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