Computational Statistics II

Please visit http://cursos.leg.ufpr.br/ce089 for full materials.

This course deals with:

1. Revision and advanced concepts of the R language
   • Objects, classes and methods
   • Algorithms and functional programming
   • Vectorization
   • Error/exception handling
   • Benchmarking and profiling
   • Dynamic documents
2. Methods for generating random numbers
   • Uniform numbers generation
   • Probability Integral Transform (PIT)
   • Acceptance/rejection methods
   • Methods based on relationships between random variables
3. Computationally intensive statistical methods
   • Monte Carlo Integration
   • Monte Carlo methods in statistical inference
   • Resampling methods: Bootstrap and jackknife
   • Application of resampling methods
   • Permutation tests
   • Markov Chains Monte Carlo Methods (MCMC)