We consider the problem of finding optimal orthogonal arrays for estimating main effects and some specified two-factor interactions. Based on theoretical results from Tang and Zhou (2009), we develop a computational algorithm for this purpose. The D-efficiency and bias are considered as the criteria for design optimality. The per-formance of the algorithm is evaluated by comparing the results obtained by the algorithm with those from complete search. Finally, we present a useful collection of optimal orthogonal arrays with small run sizes
When we want to compare two designs we usually assume the standard linear model with uncorrelated ob...
A method for constructing asymmetrical (mixed-level) designs, satisfying the balancing and interacti...
Abstract — The relationship between coding theory and the orthogonal arrays is discussed in terms of...
We study the design of two-level experiments with N runs and n factors large enough to estimate the ...
Orthogonal arrays of strength 3 permit estimation of all the main ef-fects of the experimental facto...
Designs with full estimation capacity permit estimation of all main effects and all two-factor inter...
In this thesis, we study the construction of designs for computer experiments and for screening expe...
Orthogonal arrays are widely used in industrial experiments for factor screening. Suppose only a fe...
This paper describes the construction and enumeration of mixed orthogonal arrays (MOA) to produce op...
This dissertation centers on supersaturated designs and strong orthogonal arrays, which provide usef...
Orthogonal arrays are frequently used in industrial experi-ments for quality and productivity improv...
Orthogonal arrays are frequently used in industrial experiments for quality and productivity improve...
All combinatorially inequivalent orthogonal arrays with 18 runs and eight or less factors are genera...
Abstract. Orthogonal arrays of strength 3 permit estimation of all the main effects of the experimen...
We describe a method for finding mixed orthogonal arrays of strength 2 with a large number of 2-leve...
When we want to compare two designs we usually assume the standard linear model with uncorrelated ob...
A method for constructing asymmetrical (mixed-level) designs, satisfying the balancing and interacti...
Abstract — The relationship between coding theory and the orthogonal arrays is discussed in terms of...
We study the design of two-level experiments with N runs and n factors large enough to estimate the ...
Orthogonal arrays of strength 3 permit estimation of all the main ef-fects of the experimental facto...
Designs with full estimation capacity permit estimation of all main effects and all two-factor inter...
In this thesis, we study the construction of designs for computer experiments and for screening expe...
Orthogonal arrays are widely used in industrial experiments for factor screening. Suppose only a fe...
This paper describes the construction and enumeration of mixed orthogonal arrays (MOA) to produce op...
This dissertation centers on supersaturated designs and strong orthogonal arrays, which provide usef...
Orthogonal arrays are frequently used in industrial experi-ments for quality and productivity improv...
Orthogonal arrays are frequently used in industrial experiments for quality and productivity improve...
All combinatorially inequivalent orthogonal arrays with 18 runs and eight or less factors are genera...
Abstract. Orthogonal arrays of strength 3 permit estimation of all the main effects of the experimen...
We describe a method for finding mixed orthogonal arrays of strength 2 with a large number of 2-leve...
When we want to compare two designs we usually assume the standard linear model with uncorrelated ob...
A method for constructing asymmetrical (mixed-level) designs, satisfying the balancing and interacti...
Abstract — The relationship between coding theory and the orthogonal arrays is discussed in terms of...