Search for dissertations about: "Markov Chain Monte Carlo"

Showing result 21 - 25 of 79 swedish dissertations containing the words Markov Chain Monte Carlo.

2. 21. Efficient sampling of Bayesian posteriors and predictive distributions in χEFT

   Author : Isak Svensson; Chalmers tekniska högskola; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; chiral effective field theory; Bayesian parameter estimation; nuclear physics; Markov chain Monte Carlo; two-nucleon scattering;

   Abstract : In this thesis I employ Bayesian statistics to quantify parametric and epistemic uncertainties in chiral effective field theories (χEFT) and propagate these forward to predictions of observables in low-energy nuclear physics. Two primary sources of uncertainty---experimental errors and the theoretical error induced by the truncation of the EFT at up to next-to-next-to-leading-order---are modelled and accounted for in the posterior distributions of the unknown low-energy constants (LECs) that govern interaction strengths in χEFT. READ MORE

4. 22. Statistical Segmentation and Registration of Medical Ultrasound Data

   Author : Mattias Hansson; Matematik LTH; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Registration; Segmentation; Feature descriptor; Statistical image and signal processing; Medical ultrasound; Variational methods; Mixture model; Bayesian; Markov Chain Monte Carlo; Similarity measur;

   Abstract : The interpretation of ultrasonic imagery is typically not straightforward and of quite subjective nature and therefore strongly dependent on the expertise of its users. Thus the development of algorithms which aid in the interpretation of ultrasonic data is a highly relevant topic. READ MORE

5. 23. Bayesian Inference in Large Data Problems

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

   Abstract : 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. READ MORE

6. 24. Probabilistic Modelling of Domain and Gene Evolution

   Author : Sayyed Auwn Muhammad; Jens Lagergren; Bastien Boussau; KTH; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Phylogenetics; Phylogenomics; Evolution; Domain Evolution; Gene tree; Domain tree; Bayesian Inference; Markov Chain Monte Carlo; Homology Inference; Gene families; C2H2 Zinc-Finger; Reelin Protein; Computer Science; Datalogi;

   Abstract : Phylogenetic inference relies heavily on statistical models that have been extended and refined over the past years into complex hierarchical models to capture the intricacies of evolutionary processes. The wealth of information in the form of fully sequenced genomes has led to the development of methods that are used to reconstruct the gene and species evolutionary histories in greater and more accurate detail. READ MORE

7. 25. Applications of Bayesian Econometrics to Financial Economics

   Author : Christoffer Bengtsson; Nationalekonomiska institutionen; []
   Keywords : SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; economic systems; economic theory; econometrics; Economics; systemic risk; stochastic volatility; jump-diffusion; shrinkage; covariance matrix estimation; estimation risk; portfolio selection; mean-variance optimization; Markov chain Monte Carlo; Bayesian econometrics; ekonomisk politik; ekonomiska system; ekonomisk teori; ekonometri; Nationalekonomi; economic policy;

   Abstract : This PhD thesis consists of four separate papers. What these papers have in common is that Bayesian Econometrics, in combination with Markov chain Monte Carlo (MCMC) methods, is applied to study various problems in financial economics. READ MORE