Lecture Notes

Home New Website (2016-2020) Old webpage (2001-2006) 2015: Uncertainty Quantification 2014: Big Data & Statistics 2013: Reproducible Research 2012: Continuum Mechanics 2011: Multiscale Methods 2010: Automatic Differentiation 2009: Optimization 2008: Parallel Computing 2007: Monte Carlo Methods Lecture Notes Participants Scientific Meeting 2006: Finite Element Method 2005: Inverse Problems 2004: Evolutionary PDEs 2003: Nonlinear PDEs 2002: Methods for CFD 2001: Cluster Computing	Lecture Notes Below you willl find electronic copies of the lecture notes from the 2007 Geilo Winter School on Monte Carlo Methods Morten Hjorth-Jensen Introduction to Monte Carlo Methods, Integration and Probability Distributions Random Numbers, Markov Chains, Diffusion and the Metropolis Algorithm Examples from the Physical Sciences and Sociology Laurent Bertinio and Geir Evensen Outline of Presentations The Inverse Problem Kalman Filtering The Bayes Theorem Ensemble Kalman Filter The Combined Parameter and State Estimation Problem TOPAZ - A High-Dimensional Application of the EnKF to 3D Ocean Modelling EnKF Application (to Petroleum Reservoirs) Håkon Tjelmeland Introduction to Markov Chain Monte Carlo - with Examples from Bayesian Statistics More on Markov Chain Monte Carlo Bayesian Modelling and Markov Chain Monte Carlo Fred Espen Benth Application of Monte Carlo Methods in Finance Published February 9, 2007