5,598 research outputs found
On construction of optimal mixed-level supersaturated designs
Supersaturated design (SSD) has received much recent interest because of its
potential in factor screening experiments. In this paper, we provide equivalent
conditions for two columns to be fully aliased and consequently propose methods
for constructing - and -optimal mixed-level SSDs
without fully aliased columns, via equidistant designs and difference matrices.
The methods can be easily performed and many new optimal mixed-level SSDs have
been obtained. Furthermore, it is proved that the nonorthogonality between
columns of the resulting design is well controlled by the source designs. A
rather complete list of newly generated optimal mixed-level SSDs are tabulated
for practical use.Comment: Published in at http://dx.doi.org/10.1214/11-AOS877 the Annals of
Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical
Statistics (http://www.imstat.org
Construction of optimal multi-level supersaturated designs
A supersaturated design is a design whose run size is not large enough for
estimating all the main effects. The goodness of multi-level supersaturated
designs can be judged by the generalized minimum aberration criterion proposed
by Xu and Wu [Ann. Statist. 29 (2001) 1066--1077]. A new lower bound is derived
and general construction methods are proposed for multi-level supersaturated
designs. Inspired by the Addelman--Kempthorne construction of orthogonal
arrays, several classes of optimal multi-level supersaturated designs are given
in explicit form: Columns are labeled with linear or quadratic polynomials and
rows are points over a finite field. Additive characters are used to study the
properties of resulting designs. Some small optimal supersaturated designs of
3, 4 and 5 levels are listed with their properties.Comment: Published at http://dx.doi.org/10.1214/009053605000000688 in the
Annals of Statistics (http://www.imstat.org/aos/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Screening Experiments for Simulation: A Review
This article reviews so-called screening in simulation; i.e., it examines the search for the really important factors in experiments with simulation models that have very many factors (or inputs). The article focuses on a most efficient and effec- tive screening method, namely Sequential Bifurcation. It ends with a discussion of possible topics for future research, and forty references for further study.Screening;Metamodel;Response Surface;Design
Kernelized design of experiments
This paper describes an approach for selecting instances in regression problems in the cases where observations x are readily available, but obtaining labels y is hard. Given a database of observations, an algorithm inspired by statistical design of experiments and kernel methods is presented that selects a set of k instances to be chosen in order to maximize the prediction performance of a support vector machine. It is shown that the algorithm significantly outperforms related approaches on a number of real-world datasets. --
Recent Developments in Nonregular Fractional Factorial Designs
Nonregular fractional factorial designs such as Plackett-Burman designs and
other orthogonal arrays are widely used in various screening experiments for
their run size economy and flexibility. The traditional analysis focuses on
main effects only. Hamada and Wu (1992) went beyond the traditional approach
and proposed an analysis strategy to demonstrate that some interactions could
be entertained and estimated beyond a few significant main effects. Their
groundbreaking work stimulated much of the recent developments in design
criterion creation, construction and analysis of nonregular designs. This paper
reviews important developments in optimality criteria and comparison, including
projection properties, generalized resolution, various generalized minimum
aberration criteria, optimality results, construction methods and analysis
strategies for nonregular designs.Comment: Submitted to the Statistics Surveys (http://www.i-journals.org/ss/)
by the Institute of Mathematical Statistics (http://www.imstat.org
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Minimum aberration designs for discrete choice experiments
A discrete choice experiment (DCE) is a survey method that givesinsight into individual preferences for particular attributes.Traditionally, methods for constructing DCEs focus on identifyingthe individual effect of each attribute (a main effect). However, aninteraction effect between two attributes (a two-factor interaction)better represents real-life trade-offs, and provides us a better understandingof subjects’ competing preferences. In practice it is oftenunknown which two-factor interactions are significant. To address theuncertainty, we propose the use of minimum aberration blockeddesigns to construct DCEs. Such designs maximize the number ofmodels with estimable two-factor interactions in a DCE with two-levelattributes. We further extend the minimum aberration criteria toDCEs with mixed-level attributes and develop some general theoreticalresults
LASSO-OPTIMAL SUPERSATURATED DESIGN AND ANALYSIS FOR FACTOR SCREENING IN SIMULATION EXPERIMENTS
Complex systems such as large-scale computer simulation models typically involve a large number of factors. When investigating such a system, screening experiments are often used to sift through these factors to identify a subgroup of factors that most significantly influence the interested response
A review of alternative approaches to the reduction of CO2 emissions associated with the manufacture of the binder phase in concrete
In this review we discuss a wide range of alternative approaches to the reduction of CO2 emissions associated with the manufacture of the binder phase in concrete. They are classified broadly as follows: (1) Use alternative fuels and/or alternative raw materials in the manufacture of Portland-based cements. (2) Replace Portland clinker with “low-carbon” supplementary cementitious materials (SCMs) in concrete. (3) Develop alternative low-carbon binders not based on Portland clinkers. The first approach mainly represents incremental improvements that can be achieved fairly easily and cheaply as long as suitable raw materials can be found. The second approach ranges from incremental improvements, if low levels of SCM substitution are used, all the way to major innovations for binders with very high Portland clinker replacement levels. The third approach is the most risky but also holds the greatest promise for truly significant CO2 reductions if it can be implemented on a large scale
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