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.

Item Type: Article
ISSNs: 0581-5738 (print)
Related URLs:
Subjects: Q Science > QA Mathematics
H Social Sciences > HA Statistics
Divisions : University Structure - Pre August 2011 > School of Mathematics > Statistics
ePrint ID: 29947
Accepted Date and Publication Date:
Date Deposited: 12 May 2006
Last Modified: 31 Mar 2016 11:56

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