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Old course information for spring 2009. Markov chain Monte Carlo methods for complex problems, e. Gibbs sampling and the Metropolis-Hastings algorithm. Bayesian modeling and inference. The resampling principle, both non-parametric and parametric.

Methods for constructing confidence intervals using resampling. Permutations test as an alternative to both asymptotic parametric tests and to full resampling. Examples of more complicated situations. Effective numerical calculations in resampling. The EM-algorithm for estimation in partially observed models.

Givens and Jennifer A. Hoeting Computational payday loans Statistics Second Edition (2012) and some additional handouts.

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