Introduction In this post, I outline the basics of setting up and using OpenBUGS on linux. BUGS stands for Bayesian inference Using Gibbs Sampling. OpenBUGS allows for the analysis of highly-complex statistical models using Markov-chain Monte Carlo methods. It is specifically focused on Bayesian methods. This guide may not be generalizable to all Linux systems, but it worked for me. It wasn’t too difficult, but I did have to pull together a number of different sources to get everything working as intended.
One of the first books I’ll be working (partially) through is Introduction to Linear Optimization (Bertsimas and Tsitsiklis 1997). I recently took a statistical computing class that covered a selection of optimization topics. Though the course was far from comprehensive, it highlighted the value of having a range of optimization techniques, and a thorough grounding of how they work, in your toolbox. I will be working through the first four or five chapters of this book before moving onto nonlinear programming.
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Welcome to my site! I will be using this site for a few different purposes: Writing a blog Aggregating my other publications Posting notes and exercises from my statistics and math self-study Writing short reviews of the books I read blog I used to write a lot more when I was a History of Science student at the University of Chicago. Studying statistics doesn’t give me as many opportunities to write, but I think it’s very important for people to write–and read–about statistics.
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