Includes bibliography. / 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.
Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/15852 |
Date | January 1987 |
Creators | Bust, Reg |
Contributors | Zucchini, Walter |
Publisher | University of Cape Town, Faculty of Science, Department of Statistical Sciences |
Source Sets | South African National ETD Portal |
Language | English |
Detected Language | English |
Type | Doctoral Thesis, Doctoral, PhD |
Format | application/pdf |
Page generated in 0.0024 seconds