Orthogonal models for cross-classified observations

This thesis describes methods of constructing models for cross-classified categorical data. In particular we discuss the construction of a class of approximating models and the selection of the most suitable model in the class. Examples of application are used to illustrate the methodology. The main purpose of the thesis is to demonstrate that it is both possible and advantageous to construct models which are specifically designed for the particular application under investigation. We believe that the methods described here allow the statistician to make good use of any expert knowledge which the client (typically a non-statistician) might possess on the subject to which the data relate.

Grantor dc:publisher.institution

Department of Statistical Sciences

Year dc:date.issued

1987

Author dc:creator

• Bust, Reg

Advisor dc:contributor.advisor

• Zucchini, Walter

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/11427/15852

OAI identifier oai:identifier

oai:open.uct.ac.za:11427/15852