Mathematical Sciences

Lund University

Monte Carlo methods for stochastic inference

Official Course Description

Description

Simulation based methods of statistical analysis. Markov chain methods for complex problems, e.g. Gibbs sampling and the Metropolis-Hastings algorithm. Bayesian modelling and inference. The re-sampling principle, both non-parametric and parametric. The Jack-knife method of variance estimation. Methods for constructing confidence intervals using re-sampling. Re-sampling in regression. Permutations test as an alternative to both asymptotic parametric tests and to full re-sampling. Examples of mor complicated situations. Effective numerical calculations in re-sampling. The EM-algorithm for estimation in partially observed models.

Current Sessions

Finished Sessions

Course Information

LTH Code:FMS091
NF Code: MASM11
Credits:7.5
Level:Advanced Level
Language:English

Prerequisites

Following courses

CEQ

CEQ - Monte Carlo methods for stochastic inference