mcabinaya/simulation-methods-for-stochastic-systems

My works for EE 511 - Simulation Methods For Stochastic Systems - Spring 2018 - Graduate Coursework at USC - Dr. Osonde A. Osoba

Simulation-Methods-For-Stochastic-Systems

Requirements

• Python 2.7
• Numpy >= 1.14.2
• Matplotlib >= 2.2.0
• Pandas >= 0.22.0
• Scikit-Learn >= 0.19.1
• Networkx >= 2.1

Usage

$ cd /path/to/folder 
$ python main.py 

Documents

1. Project 1.pdf and Report-1.pdf contains questions and report for:

   • 01-Distributions-Based-On-Bernoulli-Trials

   • 02-Bernoulli-Success-Counting

   • 03-Networking-Part-1

2. Project 2.pdf and Report-2.pdf contains questions and report for:

   • 004-Networking-Part-2

   • 05-Exponential-Waiting-Time

   • 06-Double-Rejection

3. Project 3.pdf and Report-3.pdf contains questions and report for:

   • 07-K-Means-Clustering-On-Old-Faithful-Data

   • 08-GMM-Expectation-Maximization

   • 09-Bag-Of-Words-Clustering

4. Project 4.pdf and Report-4.pdf contains questions and report for:

   • 10-Pi-Approximation-Using-Monte-Carlo

   • 11-Monte-Carlo-Integration-Using-Stratification

   • 12-Monte-Carlo-Integration-Using-Importance-Sampling

5. Project 5.pdf and Report-5.pdf contains questions and report for:

   • 13-MCMC-For-Sampling

   • 14-MCMC-For-Optimization

   • 15-MCMC-For-Traveling-Salesman-Problem