Constructing non-orthogonal split-split-plot designs using some resolvable block designs
نویسندگان
چکیده
منابع مشابه
factorial and split-plot statistical designs
factorial and split-plot designs are two statistical procedures used to conduct agricultural field experiments. both designs are used frequently to quantify the main and interaction effects of two or more factors. however, split-plot design is recommended for specific situations depending on major and minor goals of the study, characteristics of the factors, and precision of statistical testing...
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LetD be a resolvable 2−(v, k, λ) design, andD′ be a 2−(v′, k′, λ′) design, such that v′ = v k . Further, let r and r′ be replication numbers of a point in D and D′, respectively. Shrikhande and Raghavarao proved that then there exists a 2 − (v′′, k′′, λ′′) design D′′, such that v′′ = v, k′′ = kk′ and λ′′ = r′λ + (r − λ)λ′. If D′ is resolvable, then D′′ is also resolvable. Applying this result, ...
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For the algorithmic construction of optimal experimental designs, it is important to be able to evaluate small modifications of given designs in terms of the optimality criteria at a low computational cost. This can be achieved by using powerful update formulas for the optimality criteria during the design construction. The derivation of such update formulas for evaluating the impact of changes...
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Split-plot experiments are appropriate when some factors are more difficult and/or expensive to change than others. They require two levels of randomization resulting in a non-independent error structure. The design of such experiments has garnered much recent attention, including work on exact D-optimal split-plot designs. However, many of these procedures rely on the a priori assumption that ...
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ژورنال
عنوان ژورنال: Biometrical Letters
سال: 2020
ISSN: 1896-3811
DOI: 10.2478/bile-2020-0012