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Overview of ensemble analysis and the chain components (proposals, ...) #296
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I think this and a few of the other docs issues (e.g. #295, #294, #279) can be mostly taken care of by conscientiously making tutorials for VRDI. We should probably take care of any issues that meaningfully affect the way a user interfaces with the software (e.g. #278, #292) before spending a lot of time putting together instructional stuff. |
That's a great point. I'll try and get the ball rolling on some of the API additions/changes that I've been thinking about so that I can get proper feedback from you and everyone. |
I missed this at the time but I will have a couple of (longish) docs addressing exactly these issues ready for eyeballs next week. Right now I have it separated into one piece that just focuses on the theory side - why do we implement Markov chains this way, why check validity rather than computing transition probabilities, what types of proposals exist, etc. - and a separate doc that focuses on the implementation side with lots of specific GerryChain examples/code. There is also a geography data/preprocessing one but that needs to be updated for the new maup code. I'll send them around next week for feedback. |
Awesome! I tried to orient the |
Ok, here are some drafts. The relevant material from the MCMC_Intro is Section 7. Definitely a work in progress but hopefully this gets us off to a good start. The geography doc that gre out of VRDI last summer here: tinyurl.com/gerrydataguide |
The updated versions that we used for VRDI are here people.csail.mit.edu/ddeford/MCMC_Intro_plus.pdf |
If I'm a new user who hasn't seen ensemble analysis before, I want to get a bird's-eye view of what that is, and each of the decisions that I need to make to set it up---proposal, acceptance, constraints, initial state---with code examples.
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