An Algorithm for the Construction of "D-Optimal" Experimental Designs

Mitchell, Thomas W.

doi:10.2307/1271431

Cited by 149 publications

(86 citation statements)

References 6 publications

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“…is minimized and the correlation among the X factors is zero (or near zero) (Dykstra, 1971;Mitchell, 1974;Galil & Kiefer, 1980). A balanced matrix, in turn, has the same number of levels in each factor (Addelman, 1972;Adekeye & Kunert, 2005).…”

Section: Two-level Factorial Experimental Designs In the Presence Of mentioning

confidence: 99%

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Sequenciamento sistemático de experimentos fatoriais como alternativa à ordem aleatória

2017

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Resumo: Este trabalho tem como objetivo principal discutir o uso de métodos sistemáticos para geração de designs de experimentos com boas propriedades estatísticas e custos baixos. O foco da pesquisa é o sequenciamento dos Abstract:The current study aims to discuss the use of systematic methods to generate experimental designs with good statistical properties and low costs. The research focuses on the sequence of experiments and on analysis the results of three different approaches used to build (orthogonal and non-orthogonal) two-level factorial designs, wherein sequencing is randomly or systematically performed. The study simulated the design generated by each approach in the context of an actual glass container manufacturing process, with and without the presence of linear trend effects. The results indicate that, in comparison to the random order, systematic sequences may lead to fewer factor level changes and to increased robustness to linear trend effects. Therefore, they may attach design cost and quality.

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Section: Two-level Factorial Experimental Designs In the Presence Of mentioning

confidence: 99%

“…The first approach (hereinafter called RAN) consists of applying the DETMAX technique (Mitchell, 1974) using Statistica commercial software. The design matrix is built aiming at maximum efficiency, whereas the sequencing of its experiments is randomly done.…”

Section: Study Approachesmentioning

confidence: 99%

Sequenciamento sistemático de experimentos fatoriais como alternativa à ordem aleatória

2017

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“…The one mostly used in the robot calibration literature is DETMAX, developed in [16]. DETMAX starts with a randomly selected initial N-pose set and exchanges a pose at each iteration.…”

Section: Existing Robot Calibration Algorithmsmentioning

confidence: 99%

“…It allows the variance of the observation error to be a function of the design point. Mitchell [16] developed an algorithm called DETMAX that allows the number of design points to increase or decrease for a better search and to escape from local optima. Since then, many improvements have been made with respect to computational time and space [12], [3], [9], [22], [1], [21], [8].…”

Section: Introductionmentioning

confidence: 99%

Active robot calibration algorithm

Sun

Hollerbach

2008

2008 IEEE International Conference on Robotics and Automation

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Abstract-This paper presents a new updating algorithm to reduce the complexity of computing an observability index for kinematic calibration of robots. An active calibration algorithm is developed to include an updating algorithm in the pose selection process. Simulations on a 6-DOF PUMA robot with 27 unknown parameters shows that the proposed algorithm performs more than 50,000 times better than exhaustive search based on randomly generated designs.

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“…We chose the algorithm proposed by Federov (1972) that is often regarded as the most successful (and most time consuming) of the exchange algorithms. The algorithm is also described in Mitchell (1974).…”

Section: Selecting the Combination Of Policy Attributesmentioning

confidence: 99%

Policy options for military recruiting in the college market: Results from a national survey

Asch¹,

Du²,

Schonlau³

2004

PsycEXTRA Dataset

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The RAND Corporation is a nonprofit research organization providing objective analysis and effective solutions that address the challenges facing the public and private sectors around the world. RAND s publications do not necessarily reflect the opinions of its research clients and sponsors.RAND® is a registered trademark. © Copyright 2004 RAND CorporationAll rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in writing from RAND. PrefaceThe armed services prefer to recruit high-quality youth because of their better performance and lower attrition. However, high-quality youth are increasingly interested in attending college. While existing policies, such as the Montgomery GI Bill, that are targeted to the recruitment of the college market are likely to continue to have an effect, new policies must be developed to successfully penetrate this market and expand the supply of high-quality recruits. Indeed, the services have begun to develop programs, such as the Army's "College First" program, which allows youth to attend college prior to entry into the military and receive a college benefit provided by the military. To be fully engaged in the college market, the services may need to fine-tune these programs to enhance their effectiveness and will require a variety of programs tailored to reach different segments of the market such as college dropouts and college-bound high school youth. The purpose of the research project reported in this document is to assist the services in developing and improving programs that reach the college market. The project developed, implemented, and analyzed the results of a national survey of college youth. The survey offered respondents a series of hypothetical programs, and they were asked to rate their level of enlistment interest under each program. These programs were modeled after the Army's College First program, but varied the attributes of that program, such as the levels of college benefits and military pay and the requirements for participation. The survey data were analyzed to estimate the effects of different policy attributes on the stated level of enlistment interest. This document summarizes the final results of our study "Policy Options for Recruiting the College Market." It is intended for policy analysts and policymakers concerned about the success of military recruiting in the college market. The report builds on previous RAND studies including The RAND Corporation Quality Assurance ProcessPeer review is an integral part of all RAND research projects. Prior to publication, this document, as with all documents in the RAND monograph series, was subject to a quality assurance process to ensure that the research meets several standards, including the following: The problem is well formulated; the research approach is well designed and well executed; the data and assumptions are sound; the findings are useful and advance...

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An Algorithm for the Construction of "D-Optimal" Experimental Designs

Cited by 149 publications

References 6 publications

Sequenciamento sistemático de experimentos fatoriais como alternativa à ordem aleatória

Sequenciamento sistemático de experimentos fatoriais como alternativa à ordem aleatória

Active robot calibration algorithm

Policy options for military recruiting in the college market: Results from a national survey

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