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Generalized minimum aberration for asymmetrical fractional factorial designs

Hongquan Xu, +1 more
- 01 Aug 2001 - 
- Vol. 29, Iss: 2, pp 549-560
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TLDR
In this paper, a generalized minimum aberration criterion for comparing asymmetrical fractional factorial designs is proposed, which is independent of the choice of treatment contrasts and thus model-free.
Abstract
By studying treatment contrasts and ANOVA models, we propose a generalized minimum aberration criterion for comparing asymmetrical fractional factorial designs. The criterion is independent of the choice of treatment contrasts and thus model-free. It works for symmetrical and asymmetrical designs, regular and nonregular designs. In particular, it reduces to the minimum aberration criterion for regular designs and the minimum G 2 -aberration criterion for two-level nonregular designs. In addition, by exploring the connection between factorial design theory and coding theory, we develop a complementary design theory for general symmetrical designs, which covers many existing results as special cases.

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Experimental design

TL;DR: Experimental design is reviewed here for broad classes of data collection and analysis problems, including: fractioning techniques based on orthogonal arrays, Latin hypercube designs and their variants for computer experimentation, efficient design for data mining and machine learning applications, and sequential design for active learning.
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Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices via Stated Preference Experiments

TL;DR: This paper proposed a new causal estimand and showed that it can be nonparametrically identified and easily estimated from conjoint data using a fully randomized design, and then demonstrate the value of these techniques through empirical applications to voter decision making and attitudes toward immigrants.

Minimum moment aberration for nonregular designs and supersaturated designs

TL;DR: In this paper, a new combinatorial criterion, called minimum moment aberration, is proposed for assessing the goodness of nonregular designs and supersaturated designs, which is a good surrogate with tremendous computational advantages for many statistically justified criteria, such as minimum G2-aberrration, generalized minimum aberration and E(s2).
Journal ArticleDOI

Geometric isomorphism and minimum aberration for factorial designs with quantitative factors

TL;DR: In this article, a polynomial form of indicator functions is used to characterize the geometric structure of factorial designs with quantitative factors, and a new aberration criteria is proposed and some minimum aberration designs are presented.
Journal ArticleDOI

Uniform designs limit aliasing

Fred J. Hickernell, +1 more
- 01 Dec 2002 - 
TL;DR: In this article, it is shown that uniform designs limit the effects of aliasing to yield reasonable efficiency and robustness together, while robust experimental designs guard against inaccurate estimates caused by model misspecification.
References
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Book

The Theory of Error-Correcting Codes

TL;DR: This book presents an introduction to BCH Codes and Finite Fields, and methods for Combining Codes, and discusses self-dual Codes and Invariant Theory, as well as nonlinear Codes, Hadamard Matrices, Designs and the Golay Code.
Book

Experiments: Planning, Analysis, and Parameter Design Optimization

TL;DR: This book discusses Factorial and Fractional Factorial Experiments at Three Levels, Robust Parameter Design for Signal-Response Systems, and other Design and Analysis Techniques for Experiments for Improving Reliability.
Book

Orthogonal Arrays: Theory and Applications

Lih-Yuan Deng
TL;DR: The Rao Inequalities for Mixed Orthogonal Arrays., 9.2 The Rao InEqualities for mixed Orthogonic Arrays.- 9.4 Construction X4.- 10.1 Constructions Inspired by Coding Theory.

Introduction to coding theory

J.H. van Lint
TL;DR: This third edition has been revised and expanded, including new chapters on algebraic geometry, new classes of codes, and the essentials of the most recent developments on binary codes.