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Designing experiments for multi-variable B-spline models

Record type: Article

In a range of practical applications where a response cannot be adequately described by a low order polynomial, B-spline regression models for a single variable have proved useful for prediction. In this paper identifiable models for several explanatory variables are considered which are formulated from B-spline and monomial basis functions of known degree and with specified knots.
The use of search methods to find efficient designs under the V-, G- and D-optimality criteria is investigated. Two methods of constructing lists of feasible candidate points are described and compared across a variety of examples.

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Citation

Woods, D.C., Lewis, S.M. and Dewynne, J.N. (2003) Designing experiments for multi-variable B-spline models Sankhya, 65, pp. 660-670.

More information

Published date: 2003
Organisations: Statistics

Identifiers

Local EPrints ID: 29947
URI: http://eprints.soton.ac.uk/id/eprint/29947
ISSN: 0581-5738
PURE UUID: 28468926-8cff-43b7-9a1c-d261cf5482b4

Catalogue record

Date deposited: 12 May 2006
Last modified: 17 Jul 2017 15:56

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Contributors

Author: D.C. Woods
Author: S.M. Lewis
Author: J.N. Dewynne

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