| dc.contributor.author | Egan, Blaise | |
| dc.date.accessioned | 2010-03-25T14:50:58Z | |
| dc.date.available | 2010-03-25T14:50:58Z | |
| dc.date.issued | 2006 | |
| dc.identifier.uri | https://qmro.qmul.ac.uk/xmlui/handle/123456789/122 | |
| dc.description | Submitted in partial fulfilment of the requirements for the degree of Master of Philosophy at Queen Mary, University of London, November 2006 | en_US |
| dc.description.abstract | Classical tree models represent an attempt to create nonparametric models which
have good predictive powers as well a simple structure readily comprehensible by non-
experts. Bayesian tree models have been created by a team consisting of Chipman,
George and McCulloch and second team consisting of Denison, Mallick and Smith.
Both approaches employ Green's Reversible Jump Markov Chain Monte Carlo tech-
nique to carry out a more e®ective search than the `greedy' methods used classically.
The aim of this work is to evaluate both types of Bayesian tree models from a
Bayesian perspective and compare them. | en_US |
| dc.language.iso | en | en_US |
| dc.subject | Mathematics | en_US |
| dc.title | Tree models: a Bayesian perspective | en_US |
| dc.type | Thesis | en_US |
| dc.rights.holder | The copyright of this thesis rests with the author and no quotation from it or information derived from it may be published without the prior written consent of the author | |
