Abstract
By linear theory we mean theory concerned with problems where we get the same kind of simplification of Vg(u;θ,τ)—see (1.2.2)—as in Examples 1.3 and 1.4. This simplification occurs when
-
(i)
\(E\left( {\tilde y\left| {u,} \right.\theta ,\tau } \right) = {\theta _1}{f_1}\left( u \right) + {\theta _2}{f_2}\left( u \right) + \ldots + {\theta _k}{f_k}\left( u \right),\)f1, …,fkbeing known functions;
-
(ii)
\(\operatorname{var} \left( {\tilde y\left| {u,} \right.\theta ,\tau } \right) = \tau ;\);
-
(iii)
we are interested in estimating linearfunctions of θ.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 1980 S.D. Silvey
About this chapter
Cite this chapter
Silvey, S.D. (1980). Linear Theory. In: Optimal Design. Monographs on Applied Probability and Statistics, vol 1. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-5912-5_2
Download citation
DOI: https://doi.org/10.1007/978-94-009-5912-5_2
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-009-5914-9
Online ISBN: 978-94-009-5912-5
eBook Packages: Springer Book Archive