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| Author(s)*: | Yin, Junming | |
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| BibTeX citekey*: | Yin2005 | |
| Language: | English | |
| Title*: | Model Selection for Mixtures of Mutagenetic Trees |
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| School: | Universität des Saarlandes |
| Type of Thesis*: | Master's thesis |
| Month: | March |
| Year: | 2005 |
| LaTeX Abstract: | Mutagenetic trees constitute a particular class of restricted Bayesian tree models that have been designed to model cumulative evolutionary processes. Mixture models of mutagenetic trees have been used to model the evolution of drug resistance in the HIV genome. There exists an EM-like algorithm for estimating a K-component mutagenetic trees mixture model from data. Here we address the model selection problem of identifying the correct number of trees K. We present a modified Bayesian Information Criterion (BIC) that includes an estimate of the structural redundancy between the tree components. We compare our method to standard BIC and to cross-validation on simulated and real HIV data. We find that standard BIC tends to select evolutionary models that contain redundancy. Both cross-validation and the modified BIC perform significantly better, but the latter is more practical for real world data sets. |
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| Download Access Level: | Public |
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| 1. Referee: | Lengauer, Thomas |
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| 2. Referee: | Beerenwinkel, Niko |
| Supervisor: | Rahnenführer, Jörg |
| Status: | Completed |
| Date Kolloquium: | 19 May 2013 |
| MPG Unit: | MPI-I |
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| MPG Subunit: | D3 |
| Audience: | Expert |
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BibTeX Entry:
AUTHOR = {Yin, Junming},
TITLE = {Model Selection for Mixtures of Mutagenetic Trees},
SCHOOL = {Universit{\"a}t des Saarlandes},
YEAR = {2005},
TYPE = {Master's thesis}
MONTH = {March},
}
Entry last modified by Christine Kiesel, 12/04/2006
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