4,603 research outputs found
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
Design of Geometric Molecular Bonds
An example of a nonspecific molecular bond is the affinity of any positive
charge for any negative charge (like-unlike), or of nonpolar material for
itself when in aqueous solution (like-like). This contrasts specific bonds such
as the affinity of the DNA base A for T, but not for C, G, or another A. Recent
experimental breakthroughs in DNA nanotechnology demonstrate that a particular
nonspecific like-like bond ("blunt-end DNA stacking" that occurs between the
ends of any pair of DNA double-helices) can be used to create specific
"macrobonds" by careful geometric arrangement of many nonspecific blunt ends,
motivating the need for sets of macrobonds that are orthogonal: two macrobonds
not intended to bind should have relatively low binding strength, even when
misaligned.
To address this need, we introduce geometric orthogonal codes that abstractly
model the engineered DNA macrobonds as two-dimensional binary codewords. While
motivated by completely different applications, geometric orthogonal codes
share similar features to the optical orthogonal codes studied by Chung,
Salehi, and Wei. The main technical difference is the importance of 2D geometry
in defining codeword orthogonality.Comment: Accepted to appear in IEEE Transactions on Molecular, Biological, and
Multi-Scale Communication
Tailoring the Statistical Experimental Design Process for LVC Experiments
The use of Live, Virtual and Constructive (LVC) Simulation environments are increasingly being examined for potential analytical use particularly in test and evaluation. The LVC simulation environments provide a mechanism for conducting joint mission testing and system of systems testing when scale and resource limitations prevent the accumulation of the necessary density and diversity of assets required for these complex and comprehensive tests. The statistical experimental design process is re-examined for potential application to LVC experiments and several additional considerations are identified to augment the experimental design process for use with LVC. This augmented statistical experimental design process is demonstrated by a case study involving a series of tests on an experimental data link for strike aircraft using LVC simulation for the test environment. The goal of these tests is to assess the usefulness of information being presented to aircrew members via different datalink capabilities. The statistical experimental design process is used to structure the experiment leading to the discovery of faulty assumptions and planning mistakes that could potentially wreck the results of the experiment. Lastly, an aggressive sequential experimentation strategy is presented for LVC experiments when test resources are limited. This strategy depends on a foldover algorithm that we developed for nearly orthogonal arrays to rescue LVC experiments when important factor effects are confounded
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
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
Design of Experiments for Screening
The aim of this paper is to review methods of designing screening
experiments, ranging from designs originally developed for physical experiments
to those especially tailored to experiments on numerical models. The strengths
and weaknesses of the various designs for screening variables in numerical
models are discussed. First, classes of factorial designs for experiments to
estimate main effects and interactions through a linear statistical model are
described, specifically regular and nonregular fractional factorial designs,
supersaturated designs and systematic fractional replicate designs. Generic
issues of aliasing, bias and cancellation of factorial effects are discussed.
Second, group screening experiments are considered including factorial group
screening and sequential bifurcation. Third, random sampling plans are
discussed including Latin hypercube sampling and sampling plans to estimate
elementary effects. Fourth, a variety of modelling methods commonly employed
with screening designs are briefly described. Finally, a novel study
demonstrates six screening methods on two frequently-used exemplars, and their
performances are compared
The design of mixture experiments in the presence of covariates
Over the past three decades, the design and analysis of mixture experiments has been an active area of research, often driven by industrial applications. However, the construction of block designs for mixture experiments and trend-free orderings of the mixtures are problems that have been largely ignored until recently. These two problems form the principal subjects of this dissertation after presenting some key concepts in the design and analysis of mixture experiments;Block designs are constructed using combinatorial structures called symbolic and integral mixture mates of strength t. Certain pairs of Latin squares are a special case of symbolic mixture mates. One flexible method of constructing integral mixture mates of strength t uses the theory of trade-off for m-ary designs. In addition to mixture mates, block designs may be constructed via other methods. When the region of interest is a constrained subregion of the simplex, confounding in fractional factorial designs or asymmetrical orthogonal arrays may be used to produce orthogonal block designs. Methods for constructing non-orthogonal block designs utilizing factorial designs or orthogonal arrays in another manner are given. Finally, we formulate algorithms that allocate a given set of mixtures to blocks in such a way that an objective function is maximized;Trend-free mixture orderings allow uncorrelated estimators of mixture model parameters and deterministic trend parameters to be obtained. Deterministic trends may be induced by time effects or other lurking variables. Given a trend-free ordering of a factorial design in p - 1 factors, we illustrate how a trend-free order of mixtures can be found by transforming the p - 1 factors into p mixture variables, using one of the many transformations available, see Cornell (1991) for example. If the experimental region is a constrained subregion of the simplex, trend-free run orders are constructed using trend-free factorial designs in p - 1 factors as a template and incorporating a p-th factor by adjusting the levels of the other p - 1 components for each row. Nearly trend-free mixture orders are also found by ordering the mixtures according to an objective function
Projection-Based and Look Ahead Strategies for Atom Selection
In this paper, we improve iterative greedy search algorithms in which atoms
are selected serially over iterations, i.e., one-by-one over iterations. For
serial atom selection, we devise two new schemes to select an atom from a set
of potential atoms in each iteration. The two new schemes lead to two new
algorithms. For both the algorithms, in each iteration, the set of potential
atoms is found using a standard matched filter. In case of the first scheme, we
propose an orthogonal projection strategy that selects an atom from the set of
potential atoms. Then, for the second scheme, we propose a look ahead strategy
such that the selection of an atom in the current iteration has an effect on
the future iterations. The use of look ahead strategy requires a higher
computational resource. To achieve a trade-off between performance and
complexity, we use the two new schemes in cascade and develop a third new
algorithm. Through experimental evaluations, we compare the proposed algorithms
with existing greedy search and convex relaxation algorithms.Comment: sparsity, compressive sensing; IEEE Trans on Signal Processing 201
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