Sökning: "Bayesian inference"
Visar resultat 1 - 5 av 129 avhandlingar innehållade orden Bayesian inference.
1. Bayesian Phylogenetic Inference : Estimating Diversification Rates from Reconstructed Phylogenies
Sammanfattning : Phylogenetics is the study of the evolutionary relationship between species. Inference of phylogeny relies heavily on statistical models that have been extended and refined tremendously over the past years into very complex hierarchical models. LÄS MER
2. Bayesian Phylogenetic Inference
Sammanfattning : In this thesis we consider two very different topics in Bayesian phylogenetic inference. The first paper, "Inferring speciation and extinction rates under different sampling schemes" by Sebastian Höhna, Tanja Stadler, Fredrik Ronquist and Tom Britton, focuses on estimating the rates of speciation and extinction of species when only a subsample of the present day species is available. LÄS MER
3. Bayesian Inference in Large Data Problems
Sammanfattning : In the last decade or so, there has been a dramatic increase in storage facilities and the possibility of processing huge amounts of data. This has made large high-quality data sets widely accessible for practitioners. This technology innovation seriously challenges traditional modeling and inference methodology. LÄS MER
4. Bayesian Cluster Analysis : Some Extensions to Non-standard Situations
Sammanfattning : The Bayesian approach to cluster analysis is presented. We assume that all data stem from a finite mixture model, where each component corresponds to one cluster and is given by a multivariate normal distribution with unknown mean and variance. LÄS MER
5. Bayesian inference in probabilistic graphical models
Sammanfattning : This thesis consists of four papers studying structure learning and Bayesian inference in probabilistic graphical models for both undirected and directed acyclic graphs (DAGs).Paper A presents a novel algorithm, called the Christmas tree algorithm (CTA), that incrementally construct junction trees for decomposable graphs by adding one node at a time to the underlying graph. LÄS MER