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Journal ArticleDOI

The design of optimum multifactorial experiments

R. L. Plackett, +1 more
- 01 Jun 1946 - 
- Vol. 33, Iss: 4, pp 305-325
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This article is published in Biometrika.The article was published on 1946-06-01. It has received 3546 citations till now.

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Book ChapterDOI

On the Experimental Attainment of Optimum Conditions

TL;DR: The work described in this article is the result of a study extending over the past few years by a chemist and a statistician, which has come about mainly in answer to problems of determining optimum conditions in chemical investigations, but they believe that the methods will be of value in other fields where experimentation is sequential and the error fairly small.
Journal Article

Factorial sampling plans for preliminary computational experiments

Max D. Morris
- 01 Jan 1992 - 
TL;DR: The proposed experimental plans are composed of individually randomized one-factor-at-a-time designs, and data analysis is based on the resulting random sample of observed elementary effects, those changes in an output due solely to changes in a particular input.
Journal ArticleDOI

Some New Three Level Designs for the Study of Quantitative Variables

TL;DR: In this paper, a class of incomplete three level factorial designs useful for estimating the coefficients in a second degree graduating polynomial are described and the designs either meet, or approximately meet, the criterion of rotatability and for the most part can be orthogonally blocked.
Journal ArticleDOI

Factorial sampling plans for preliminary computational experiments

TL;DR: In this article, the problem of designing computational experiments to determine which inputs have important effects on an output is considered, and experimental plans are composed of individually randomized one-factor-at-a-time designs, and data analysis is based on the resulting random sample of observed elementary effects.
Journal ArticleDOI

Metamodels for Computer-Based Engineering Design: Survey and Recommendations

TL;DR: This paper surveys their existing application in engineering design, and addresses the dangers of applying traditional statistical techniques to approximate deterministic computer analysis codes, along with recommendations for the appropriate use of statistical approximation techniques in given situations.