On Practical Use of the Concept of D-Optimality

Nalimov, V. V.; Golikova, T. I.; Mikeshina, Nadezhda G.

doi:10.2307/1267326

Cited by 9 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These other designs will only be briefly mentioned here because they have not been found clearly superior (Lucas 1976(Lucas , 1978. Nalimov (1970), Pesotchinsky (1975) and Mitchell and Bayne (1978) have attempted to develop optimum or near optimum designs for second order equations. These designs may be useful in special situations.…”

Section: Second Order Designsmentioning

confidence: 99%

Response Surface Experimentation

Thompson

1982

J Food Processing Preservation

132

View full text Add to dashboard Cite

Section: Second Order Designsmentioning

confidence: 99%

Response Surface Experimentation

Thompson

1982

J Food Processing Preservation

132

View full text Add to dashboard Cite

“…The approximate D-, and equivalently G-, optimal design for the secondorder model was given by Nalimov, Golikova, and 6 (-1, -1), (-1, 1), (1, -1), (0, 0), (0, 1), (1, 0) 144.0 .9667 5.667 7 (-1, -1), (-1, 1), (1, -1), (1, 1), (0, 0), (0, -1), (1, 0) 960.0 .6656 1.407 8 (-1, -1), (-1, 1), (1, -1), (1, 1), 2x(0, 0), (0, 1), (1, 0) 1,664.0 .5218 1.319 9 (-1, -1), (-1, 1), (1, -1), (1, 1), 2x(0, 0), (-1, 0), (0, -1), (0, 1) 3,840.0 .4389 1.100 Mikeshina (1970) and by Atkinson (1973), and the approximate I-optimal design can be readily derived using the approach of Cook and Nachtsheim (1982). The approximate D-, and equivalently G-, optimal design for the secondorder model was given by Nalimov, Golikova, and 6 (-1, -1), (-1, 1), (1, -1), (0, 0), (0, 1), (1, 0) 144.0 .9667 5.667 7 (-1, -1), (-1, 1), (1, -1), (1, 1), (0, 0), (0, -1), (1, 0) 960.0 .6656 1.407 8 (-1, -1), (-1, 1), (1, -1), (1, 1), 2x(0, 0), (0, 1), (1, 0) 1,664.0 .5218 1.319 9 (-1, -1), (-1, 1), (1, -1), (1, 1), 2x(0, 0), (-1, 0), (0, -1), (0, 1) 3,840.0 .4389 1.100 Mikeshina (1970) and by Atkinson (1973), and the approximate I-optimal design can be readily derived using the approach of Cook and Nachtsheim (1982).…”

Section: Design Detailsmentioning

confidence: 99%

The Application of the Annealing Algorithm to the Construction of Exact Optimal Designs for Linear-Regression Models

Haines¹

1987

Technometrics

View full text Add to dashboard Cite

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.This article reports the application of the annealing algorithm to the construction of exact D-, I-, and G-optimal designs for polynomial regression of degree 5 on the interval [-1, 1] and for the second-order model in two factors on the design space [-1, 1] x [-1, 1]. Details of the perturbation scheme and the annealing schedules used are given, and the method of implementation is illustrated by means of a simple example. The algorithm is assessed by comparing its performance, in terms of computer time and efficiency, with the modified Fedorov procedure, and it is shown to be particularly effective in finding G-optimal designs. The salient features of the exact designs constructed in this study are also summarized.

show abstract