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    Tree models: a Bayesian perspective 
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    Tree models: a Bayesian perspective

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    MPhil_Thesis_Egan_Blaise_F.pdf (813.5Kb)
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    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.
    Authors
    Egan, Blaise
    URI
    https://qmro.qmul.ac.uk/xmlui/handle/123456789/122
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    • Theses [3321]
    Copyright statements
    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
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