Search for dissertations about: "Markov chain Monte Carlo"

Showing result 1 - 5 of 79 swedish dissertations containing the words Markov chain Monte Carlo.

2. 1. Semi Markov chain Monte Carlo

   Author : Håkan Ljung; Uppsala universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Mathematics; Adaptive simulation; error-in-the-variables; Kullback-Leibler divergence; Markov chain simulation; Markov chain Monte Carlo; semi-regenerative; MATEMATIK; MATHEMATICS; MATEMATIK; matematisk statistik; Mathematical Statistics;

   Abstract : The first paper introduces a new simulation technique, called semi Markov chain Monte Carlo, suitable for estimating the expectation of a fixed function over a distribution π, Eπf(χ). Given a Markov chain with stationary distribution p, for example a Markov chain corresponding to a Markov chain Monte Carlo algorithm, an embedded Markov renewal process is used to divide the trajectory into different parts. READ MORE

4. 2. Financial Applications of Markov Chain Monte Carlo Methods

   Author : Andreas Graflund; Nationalekonomiska institutionen; []
   Keywords : 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;

   Abstract : This thesis consists of four empirical studies on financial economics. The first chapter contains a short summary of the thesis. READ MORE

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

   Author : Federica Milinanni; Pierre Nyquist; Mark Clements; KTH; []
   Keywords : 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;

   Abstract : 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. READ MORE

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

   Author : Anna Wigren; Fredrik Lindsten; Lawrence Murray; Riccardo Sven Risuleo; Simon Maskell; Uppsala universitet; []
   Keywords : 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;

   Abstract : 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. READ MORE

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

   Author : Johan Dahlin; Thomas B. Schön; Fredrik Lindsten; Richard Everitt; Linköpings universitet; []
   Keywords : 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;

   Abstract : 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. READ MORE