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IMPRS Publications :: Thesis :: Yin, Junming


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Thesis - Master's thesis | @MastersThesis | Masterarbeit


Author
Author(s)*:Yin, Junming
BibTeX citekey*:Yin2005
Language:English

Title, School
Title*:Model Selection for Mixtures of Mutagenetic Trees
School:Universität des Saarlandes
Type of Thesis*:Master's thesis
Month:March
Year:2005


Note, Abstract, Copyright
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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Referees, Status, Dates
1. Referee:Lengauer, Thomas
2. Referee:Beerenwinkel, Niko
Supervisor:Rahnenführer, Jörg
Status:Completed
Date Kolloquium:3 September 2014

Correlation
MPG Unit:MPI-I
MPG Subunit:D3
Audience:Expert
Appearance:MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort

BibTeX Entry:

@MASTERSTHESIS{Yin2005,
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},
}



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