Table of Contents
A set of simple tutorials that explain MCMC (Markov Chain Monte Carlo).
A short description of the motivation behind the creation and maintenance of the project. This should explain why the project exists.
Local Usage
Installing Jupyter: Before you play around with our tutorial, first install Jupyter Notebook:
pip install jupyterPlease note that if pip is connected to Python 2.7 on your computer, then you can also try pip3. You can also install Anaconda Python 3.6, which downloads both Python 3.6 and Jupyter.
Cloning Repo & Starting Jupyter Server: After you have installed Jupyter, run the following commands:
# Clone the tutorial repo
git clone https://github.com/MUSSLES/tutorials.git
# Go to the repo directory
cd MCMC_Tutorial
# Start the Jupyter server
jupyter notebookAfter executing the last command, you should be redirected to a localhost server in your browser. Click on the tutorials you want to view, which are listed above... and have a blast!
TODO
Please enjoy the code and offer us any suggestions. It is our aim to make the tutorials accessible and usable by all, so that anyone can easily pick up MCMC thinking. We are always interested to hear about potential improvements to the tutorial... suggestions and pull requests are highly encouraged!
Questions? Tony Wong (anthony.e.wong@colorado.edu)
 John Letey 💻 |
 Nihar Nandan 💻 |
 Mingxuan Zhang 💻 |
 Tony Wong 💻 |
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Copyright 2018 Tony Wong, H. Nihar Nandan, John Letey, Mingxuan Zhang
This file is part of MUSSLES (Modeling and Uncertainty in Storm and Sea LEvelS). MUSSLES is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.