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In practice, fractional factorial split-plot (FFSP) designs are widely used when the levels of some factors are very difficult to change or control. The factors of an FFSP design are divided into two ...
Orthogonal array based-Latin hypercubes, also called U designs, have popularly been adopted for designing a computer experiment. The relationship between the averaged squared discrepancy of all U desi...
We consider sliced computer experiments where priori knowledge suggests that factors may have different levels of importance, and so some factors need to be paid more attention than others. A new clas...
Uniform design is to seek its design points to be uniformly scattered on the experimental domain under some discrepancy measure. In this paper all the design points of a full factorial design can be s...
The response of a patient in a clinical trial usually depends on both the se-lected treatment and some latent covariates, while its variance varies across the treatment groups. A general heteroscedast...
Orthogonal array based-Latin hypercubes, also called U designs, have popularly been adopted for designing a computer experiment. The relationship between the averaged squared discrepancy of all U desi...
Latin squares have been widely used to design an experiment where the blocking factors and treatment factors are of the same levels. For some experiments, the size of blocks may be less than the numbe...
Orthogonal Latin hypercube (OLH) is a good choice for computer experiments be-cause it ensures independent estimation of linear effects when a first-order model is fitted.However, when second-order ef...
In this paper we show how the approach of spectral analysis generalizes the standard ANOVA-based techiques for studying data from designed experiments.Several examples are worked out in detail, includ...
Partially balance incomplete block (PBIB) design is based on association scheme. There are many kinds of association schemes and the structure of association scheme itself is an important object in co...
Based on the hierarchical ordering principle of factorial effects in experimental design, we propose an aliased effect-number pattern (AENP) as a criterion to judge a two-level regular design; such a ...
A-optimal designs for generalized linear model with two parameters.

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