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D-optimal two-level parallel-flats block designs with partial replication

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Abstract Under the assumption of random block effects, a new class of two-level factorial block designs with partial replication is proposed for estimating the user-specified requirement sets and variance components.… Click to show full abstract

Abstract Under the assumption of random block effects, a new class of two-level factorial block designs with partial replication is proposed for estimating the user-specified requirement sets and variance components. A noteworthy feature of the proposed designs is that the within-block and between-block replicates are both conducted, such that the components of variance can be unbiasedly estimated. Under the framework of parallel-flats block designs, a set of sufficient conditions is presented for design characterization, and an algorithm is developed for systematically constructing the proposed designs. Using the proposed algorithm, a design catalogue is generated as a reference for experimentation. Some examples are given to demonstrate that the proposed designs are promising alternatives for practical applications.

Keywords: two level; block designs; parallel flats; designs partial; partial replication; flats block

Journal Title: Journal of Statistical Planning and Inference
Year Published: 2018

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