Search for dissertations about: "multilevel Monte Carlo"

Showing result 1 - 5 of 14 swedish dissertations containing the words multilevel Monte Carlo.

2. 1. Computational Aspects of Lévy-Driven SPDE Approximations

   Author : Andreas Petersson; Göteborgs universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; multilevel Monte Carlo; numerical approximation of stochastic differential equations; multiplicative noise; Lévy processes; finite element method; variance redons; Monte Carlo; weak convergence; Lévy processes;

   Abstract : In order to simulate solutions to stochastic partial differential equations (SPDE) they must be approximated in space and time. In this thesis such fully discrete approximations are considered, with an emphasis on finite element methods combined with rational semigroup approximations. There are several notions of the error resulting from this. READ MORE

4. 2. Approximating Stochastic Partial Differential Equations with Finite Elements: Computation and Analysis

   Author : Andreas Petersson; Chalmers tekniska högskola; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Lévy process; Lyapunov equation; white noise; finite element method; multilevel Monte Carlo; Monte Carlo; multiplicative noise; asymptotic mean square stability; stochastic heat equation; covariance operator; weak convergence; generalized Wiener process; numerical approximation; stochastic wave equation; Stochastic partial differential equations;

   Abstract : Stochastic partial differential equations (SPDE) must be approximated in space and time to allow for the simulation of their solutions. In this thesis fully discrete approximations of such equations are considered, with an emphasis on finite element methods combined with rational semigroup approximations. READ MORE

5. 3. Coarse Graining Monte Carlo Methods for Wireless Channels and Stochastic Differential Equations

   Author : Håkon Hoel; Anders Szepessy; Ola Hössjer; KTH; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Coarse graining; Monte Carlo Methods; Stochastic processes; Numerical analysis; Numerisk analys;

   Abstract : This thesis consists of two papers considering different aspects of stochastic process modelling and the minimisation of computational cost. In the first paper, we analyse statistical signal properties and develop a Gaussian pro- cess model for scenarios with a moving receiver in a scattering environment, as in Clarke’s model, with the generalisation that noise is introduced through scatterers randomly flip- ping on and off as a function of time. READ MORE

6. 4. Issues of Complex Hierarchical Data and Multilevel Analysis : Applications in Empirical Economics

   Author : Joel Karlsson; Ghazi Shukur; Håkan Locking; Scott Hacker; Linnéuniversitetet; []
   Keywords : SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; Multilevel modelling; Hierarchical modelling; Single farm payments; Part-time unemployment; Educational attainment; Performance evaluation; Economics; Nationalekonomi;

   Abstract : This thesis consists of four individual essays and an introduction chapter. The essays are in the field of multilevel analysis of economic data. The first essay estimates capitalisation effects of farm attributes, with a particular focus on single farm payments (SFP), into the price of farms. READ MORE

7. 5. Multiscale Methods and Uncertainty Quantification

   Author : Daniel Elfverson; Axel Målqvist; Frédéric Legoll; Uppsala universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; multiscale methods; finite element method; discontinuous Galerkin; Petrov-Galerkin; a priori; a posteriori; complex geometry; uncertainty quantification; multilevel Monte Carlo; failure probability; Beräkningsvetenskap med inriktning mot numerisk analys; Scientific Computing with specialization in Numerical Analysis;

   Abstract : In this thesis we consider two great challenges in computer simulations of partial differential equations: multiscale data, varying over multiple scales in space and time, and data uncertainty, due to lack of or inexact measurements.We develop a multiscale method based on a coarse scale correction, using localized fine scale computations. READ MORE