Computational Statistics II
Please visit http://cursos.leg.ufpr.br/ce089 for full materials.
This course deals with:
- 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
- Methods for generating random numbers
- Uniform numbers generation
- Probability Integral Transform (PIT)
- Acceptance/rejection methods
- Methods based on relationships between random variables
- 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)