Designing experiments for multi-variable B-spline models
Woods, D.C., Lewis, S.M. and Dewynne, J.N. (2003) Designing experiments for multi-variable B-spline models. Sankhya, 65, 660-670.
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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.
|Subjects:||Q Science > QA Mathematics
H Social Sciences > HA Statistics
|Divisions:||University Structure - Pre August 2011 > School of Mathematics > Statistics
|Date Deposited:||12 May 2006|
|Last Modified:||02 Mar 2012 12:47|
|Contributors:||Woods, D.C. (Author)
Lewis, S.M. (Author)
Dewynne, J.N. (Author)
|Contact Email Address:||D.C.Woods@maths.soton.ac.uk|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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