Sökning: "Markov Chain Monte Carlo Methods"

Visar resultat 1 - 5 av 57 avhandlingar innehållade orden Markov Chain Monte Carlo Methods.

  1. 1. Financial Applications of Markov Chain Monte Carlo Methods

    Författare :Andreas Graflund; Nationalekonomiska institutionen; []
    Nyckelord :SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; Finansiering; Financial science; ekonomiska system; ekonomisk politik; ekonomisk teori; Nationalekonomi; economic policy; economic systems; economic theory; Economics; econometrics; Mean Reversion; Diversification; Real Estate Stocks; Markov Chain Monte Carlo Methods; Stock Markets; ekonometri;

    Sammanfattning : This thesis consists of four empirical studies on financial economics. The first chapter contains a short summary of the thesis. LÄS MER

  3. 2. Markov Chain Monte Carlo Methods and Applications in Neuroscience

    Författare :Federica Milinanni; Pierre Nyquist; Mark Clements; KTH; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Markov chain Monte Carlo; Large deviations; Subcellular pathway models; Markov chain Monte Carlo; Stora avvikelser; Subcellular pathway models; Tillämpad matematik och beräkningsmatematik; Applied and Computational Mathematics;

    Sammanfattning : An important task in brain modeling is that of estimating model parameters and quantifying their uncertainty. In this thesis we tackle this problem from a Bayesian perspective: we use experimental data to update the prior information about model parameters, in order to obtain their posterior distribution. LÄS MER

  4. 3. Sequential Monte Carlo methods for conjugate state-space models

    Författare :Anna Wigren; Fredrik Lindsten; Lawrence Murray; Riccardo Sven Risuleo; Simon Maskell; Uppsala universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Sequential Monte Carlo; Particle filter; Markov chain Monte Carlo; Conjugacy; State-space model; Probabilistic programming; Electrical Engineering with specialization in Signal Processing; Elektroteknik med inriktning mot signalbehandling;

    Sammanfattning : Bayesian inference in state-space models requires the solution of high-dimensional integrals, which is intractable in general. A viable alternative is to use sample-based methods, like sequential Monte Carlo, but this introduces variance into the inferred quantities that can sometimes render the estimates useless. LÄS MER

  5. 4. Accelerating Monte Carlo methods for Bayesian inference in dynamical models

    Författare :Johan Dahlin; Thomas B. Schön; Fredrik Lindsten; Richard Everitt; Linköpings universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Computational statistics; Monte Carlo; Markov chains; Particle filters; Machine learning; Bayesian optimisation; Approximate Bayesian Computations; Gaussian processes; Particle Metropolis-Hastings; Approximate inference; Pseudo-marginal methods;

    Sammanfattning : Making decisions and predictions from noisy observations are two important and challenging problems in many areas of society. Some examples of applications are recommendation systems for online shopping and streaming services, connecting genes with certain diseases and modelling climate change. LÄS MER

  7. 5. Machine learning using approximate inference : Variational and sequential Monte Carlo methods

    Författare :Christian Andersson Naesseth; Thomas Schön; Fredrik Lindsten; Iain Murray; Linköpings universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY;

    Sammanfattning : Automatic decision making and pattern recognition under uncertainty are difficult tasks that are ubiquitous in our everyday life. The systems we design, and technology we develop, requires us to coherently represent and work with uncertainty in data. LÄS MER