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1. 1. Bayesian Inference in Large Data Problems

   Författare :Matias Quiroz; Mattias Villani; Bani K. Mallick; Stockholms universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Bayesian inference; Large data sets; Markov chain Monte Carlo; Survey sampling; Pseudo-marginal MCMC; Delayed acceptance MCMC; Statistics; statistik;

   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

3. 2. Bayesian inference in probabilistic graphical models

   Författare :Felix Leopoldo Rios; Tatjana Pavlenko; Alun Thomas; KTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Graphical models; Bayesian inference; predictive classification; decomposable graphs; Tillämpad matematik och beräkningsmatematik; Applied and Computational Mathematics;

   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

4. 3. Essays on Bayesian Inference for Social Networks

   Författare :Johan Koskinen; Ove Frank; Philippa Pattison; Stockholms universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Bayesian inference; social network analysis; Markov chain Monte Carlo; exponential random graphs; cognitive social structures; longitudinal social networks.; Statistics; Statistik;

   Sammanfattning : This thesis presents Bayesian solutions to inference problems for three types of social network data structures: a single observation of a social network, repeated observations on the same social network, and repeated observations on a social network developing through time.A social network is conceived as being a structure consisting of actors and their social interaction with each other. LÄS MER

5. 4. Bayesian inference for detection problems in biology

   Författare :Ronny Hedell; Göteborgs universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; PCR; Bayesian inference; Forensic DNA analysis; Syndromic surveillance; Bacillus anthracis; Markov chain Monte Carlo; Allele dropout; Bacillus anthracis;

   Sammanfattning : This thesis is about different kinds of detection problems in biology: detection of DNA sequences in crime scene samples, detection of harmful bacteria in feed and food stuff and detection of epidemical diseases in animal populations. In each case, biological data is produced or collected in order to determine which DNA sequences, bacteria types or diseases are present, if any. LÄS MER

7. 5. Analytical Approximations for Bayesian Inference

   Författare :Tohid Ardeshiri; Fredrik Gustafsson; Johan Wolfgang Koch; Linköpings universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY;

   Sammanfattning : Bayesian inference is a statistical inference technique in which Bayes’ theorem is used to update the probability distribution of a random variable using observations. Except for few simple cases, expression of such probability distributions using compact analytical expressions is infeasible. LÄS MER