Abstract
In this section, we develop a direct sum decomposition for the estimation space of an effectively balanced model. Our aim is to develop an eigenspace decomposition, and in the next section we will give conditions under which the direct sum decomposition of this section is also an eigenspace decomposition. The manner in which we view the estimation space and its components is rather non-standard. We feel that our approach is very comprehensive, yet its applications are free of the tedious algebra that one often encounters in similar results. Thus we try to give our reader some idea of how and where our results fit into the field of experimental design. Whether this approach will lead to new insights into the properties of obscure experimental designs is moot and outside the scope of this thesis.
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
© 1982 Springer-Verlag New York Inc.
About this chapter
Cite this chapter
Mclntosh, A. (1982). Applications: The Non-Full Rank Case. In: Fitting Linear Models. Lecture Notes in Statistics, vol 10. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-5752-3_4
Download citation
DOI: https://doi.org/10.1007/978-1-4612-5752-3_4
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-90746-8
Online ISBN: 978-1-4612-5752-3
eBook Packages: Springer Book Archive