Mathematical Statistics: Monte Carlo Methods for Statistical Inference

Education facts

Code: MASM11

<p>How to use a computer to generate random numbers and how to use these number to solve mathematical and statistical problems.</p><p>The course gives an overview of 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.</p>

Entry requirements

For admission to the course knowledge equivalent to at least one of the courses MASC13, Markov processes, 7.5 credits or MASC14, Stationary Stochastic processes, 7.5 credits are required together with English B.

Education offerings

Each offering has its own dates and conditions. Closed offerings are retained as history and do not mean that a new application is open.

• Mathematical Statistics: Monte Carlo Methods for Statistical Inference

  Lund University

  Lund

  Start date: 18 January 2027

  End date: 28 March 2027

  Pace of study: 50 %