| The aim of this course is to teach the students the basic modeling and simulation techniques used in applied stochastic analysis. With many vivid examples from science and engineering, the students are expected to grasp the probabilistic ideas and apply them into their own research fields. |
Lect1 Introduction (notes)
Lect2 Random Variables (notes)
Lect3 Generation of Random Variables (notes)
Lect4 Variance Reduction (notes)
Lect5 Limit Theorems (notes)
Lect6 Markov Chains (notes)
Lect7 Metropolis Algorithm (notes)