Modelling And Simulation

Module Title:
Modelling and Simulation
Module Code:

Module Content
  • Random number generation: pseudo random number generators.
  • Simulating samples from discrete distributions.
  • Simulating samples from continuous distributions: the inverse transform method, rejection sampling,
  • Simulating statistical models: multivariate normal distributions, hierarchical models (Bayesian models, mixture distributions), Markov chains.
  • Monte Carlo methods: Studying models via simulation, Monte Carlo estimates, variance reduction, and applications to statistical learning.Markov Chain Monte Carlo (MCMC) methods: the Metropolis-Hastings method, Convergence of MCMC methods, applications to Bayesian learning.
  • Resampling methods: bootstrap estimates, applications to machine learning.