Found 4 relevant results in 1.11s where lecturer="Andrew Barbour"

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Bioinformatics: in-depth

Bioinformatik: Vertiefung

551-1296-00L 2004S , 2005S , 2006S , 2007S , 2008S 4 Credits BSC , MSC D-CHAB , D-PHYS , D-MAVT , D-BIOL , D-MATH , D-HEST , D-ITET

Study of mathematical methods and algorithms in bioinformatics: Topics: Probability and statistics (prerequisites, statistical estimation, Markov chains, evolutionary models, sequence alignment), Hidden Markov models (Viterbi algorithm), Bayesian networks (principles, network inference), sequence alignment and phylogenetic trees (evolutionary relations, multiple sequence alignment, tree building).

2004S
2005S
2006S
2007S

Seminar on Statistics: Bayesian Statistics

Seminar über Statistik: Bayesian Statistics

401-3620-08L 2008S 6 Credits BSC , MSC D-MATH

The seminar discusses the Bayesian paradigm where also the unknown parameters are considered as random variables. Topics include prior, posterior and likelihood, differences to frequentist statistics, empirical Bayes procedures, nonparametric Bayesian methods, asymptotic properties of the posterior, model selection and computational methods.

Seminar on Statistics: Inverse Problems in Statistics

Seminar über Statistik: Inverse Problems in Statistics

401-3620-07L 2007S 6 Credits BSC , MSC D-MATH

Examples of inverse problems are Wicksell's problem,censoring, deconvolution and the indirect regression model.We study minimax lower bounds, plug-in and(nonparametric) maximum likelihood estimators, andalgorithms for computing the maximum likelihood estimator,such as the EM algorithm. Also the asymptotic propertiesof the estimators are examined.

401-3620-00L 2006S 6 Credits

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