Sökning: "Gibbs sampler"

Visar resultat 1 - 5 av 10 avhandlingar innehållade orden Gibbs sampler.

  1. 1. Bayesian Cluster Analysis : Some Extensions to Non-standard Situations

    Författare :Jessica Franzén; Daniel Thorburn; Jukka Corander; Stockholms universitet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; Cluster analysis; Clustering; Classification; Mixture model; Gaussian; Bayesian inference; MCMC; Gibbs sampler; Deviant group; Longitudinal; Missing data; Multiple imputation; Statistics; Statistik; statistik; Statistics;

    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

  2. 2. A Bayesian approach to retrospective detection of change-points in road surface measurements

    Författare :Fridtjof Thomas; Urban Hjort; Chalmers Tekniska högskola; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; Change-point detection; retrospective view; autoregressive processes; minimal imaginary training sample; road surface measurements; international roughness index; rutting; Laser-RST vehicles; road maintenance; pavement management; statistik; Statistics;

    Sammanfattning : First-order autoregressive processes are analysed for sudden changes in parameter value. In its most general form, a multivariate vector of measurements is allowed, and no prior knowledge about the involved parameters is required. LÄS MER

  3. 3. Particle filters and Markov chains for learning of dynamical systems

    Författare :Fredrik Lindsten; Thomas B. Schön; Lennart Ljung; Fredrik Gustafsson; Arnaud Doucet; Linköpings universitet; []
    Nyckelord :ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; TEKNIK OCH TEKNOLOGIER; NATURAL SCIENCES; ENGINEERING AND TECHNOLOGY; Bayesian learning; System identification; Sequential Monte Carlo; Markov chain Monte Carlo; Particle MCMC; Particle filters; Particle smoothers;

    Sammanfattning : Sequential Monte Carlo (SMC) and Markov chain Monte Carlo (MCMC) methods provide computational tools for systematic inference and learning in complex dynamical systems, such as nonlinear and non-Gaussian state-space models. This thesis builds upon several methodological advances within these classes of Monte Carlo methods. LÄS MER

  4. 4. Towards a Model of General Text Complexity for Swedish

    Författare :Johan Falkenjack; Arne Jönsson; Robert Östling; Linköpings universitet; []

    Sammanfattning : In an increasingly networked world, where the amount of written information is growing at a rate never before seen, the ability to read and absorb written information is of utmost importance for anything but a superficial understanding of life's complexities. That is an example of a sentence which is not very easy to read. LÄS MER

  5. 5. Bayesian inference in probabilistic graphical models

    Författare :Felix Leopoldo Rios; Tatjana Pavlenko; Alun Thomas; KTH; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; 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