0.1 ESMA5015.pdf
0.2 Syllabus
0.3 Assignments
0.4 Resma3.RData (Ver 3.2)
1.1 Installation and updating
1.2 R Markdown, HTML and Latex
1.3 R basics
1.4 Programming in R
1.5 Random numbers and simulation
1.6 Graphs with ggplot2
1.7 List of base R commands
3.1 Introduction
3.2 Conditional Probability and Independence
3.3 Random Variables and Random Vectors
3.4 Expectation
3.5 Inequalities and Limit Theorems
3.6 Transformations
3.7 Discrete Distributions
3.8 Continuous Distributions
4.1 General Methods
4.2 Fundamental Theorem
4.3 Special Cases
5.1 Basic Statistics
5.3 Verifying a Simulation
5.3 A Realistic Example
6.1 Discrete - Time Markov Chains
6.2 MCMC - Markov Chain Monte Carlo
6.3 Monitoring Convergence
6.4 Gibbs Sampler
6.5 Slice Sampler
6.6 Bayesian Inference for Normal Distribution
6.7 On/Off Problem
7.1 Antithetic and Control Variables
7.2 Conditioning and Importance Sampling
8.1 Optimization
8.2 EM algorithm
8.3 The Symmetric Random Walk in R
9.1 Risk!
9.2 Waiting Time