The Annals of Statistics

Computation of the Optimum Designs Under Singular Information Matrices

Andrej Pazman

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Abstract

The main result of this paper is that $g$-inverses are not needed for computing optimum designs when the singularity of the information matrix is unavoidable. They are, of course, needed for the analysis. It will be shown that it is possible to augment the experimental region so that procedures for computing optimum designs for $s$ out $k$ parameters $(s < k)$ which are developed for the nonsingular case may also be used for the singular case.

Article information

Source
Ann. Statist., Volume 6, Number 2 (1978), 465-467.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176344137

Digital Object Identifier
doi:10.1214/aos/1176344137

Mathematical Reviews number (MathSciNet)
MR483216

Zentralblatt MATH identifier
0386.62067

JSTOR
links.jstor.org

Subjects
Primary: 62K05: Optimal designs

Keywords
Experimental design singular information matrices $g$-inverses

Citation

Pazman, Andrej. Computation of the Optimum Designs Under Singular Information Matrices. Ann. Statist. 6 (1978), no. 2, 465--467. doi:10.1214/aos/1176344137. https://projecteuclid.org/euclid.aos/1176344137


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