ESMA 5015 Simulation

General Syllabus
List of Stories of the Data sets
Homeworks and Exams
Some Basic Ideas and Concepts Introduction to ESMA 5015
R An Introduction to R
R Programing Language and User-Written Functions
Extending R
Some R Commands
Simulation An Example: Monopoly
Probability Introduction
Conditional Probability and Independence
Random Variables and Random Vectors
Expectation of a R.V.
Functions of a R.V. - Transformations
Inequalities and Limit Theorems
Some Standard Distributions Discrete Distributions
Continuous Distributions
Generating Random Variables General Methods
Fundamental Theorem of Simulation
Special Cases
Statistics Basic Statistics
Verifying the Simulation
A Realistic Example
Stochastic Processes Discrete - Time Markov Chains
MCMC - Markov Chain Monte Carlo
The Gibbs Sampler
The Slice Sampler
Bayesian Inference for Normal Distribution
Variance Reduction Methods Antithetic and Control Variables
Conditioning and Importance Sampling
Stochastic Optimization Stochastic Optimization and Simulated Annealing
The EM Algorithm
Larger Simulations The Symmetric Random Walk in Rd
Random Walk - Routines and Data
  Estimating the Waiting Time