Requesting feedback on 1. issue design, and 2. contents of issue @kgostic @seabbs @parksw3

This looks good to me. I think we might also want to consider:

• Visualising the delay data as an initial step
• Posterior predictions for a single or both models (may be included in your above)
• Translating a fitted distribution to a pmf (this is most likely of my suggestions to be out of scope here)

I agree with @seabbs. Structure of the issue looks great. Visualizing the delay and generating posterior predictions are both in scope and should be included.

Translating a fitted distribution to a pmf (this is most likely of my suggestions to be out of scope here)
I would also like this to be in scope! I think it's important.

From our previous discussion, it sounded like the main blocker is that @seabbs would like the function used to convert the fitted pdf into a double censored (discrete) pmf to live in another yet-to-be-created package that doesn't require heavy stan dependencies. I'd propose just putting that function here for now or using an existing one from epinow2 or epinowcast until it can be moved?

I'd propose just putting that function here for now or using an existing one from epinow2 or epinowcast until it can be moved?

Yes either this or just using a placeholder function name for now and seeing where we are when we get to this point

@athowes, here's the relevant function from epinowcast: https://github.com/epinowcast/epinowcast/blob/e9a7a7cc9c2e02bab20491edea3bc0dc5ec2899b/R/model-module-helpers.R#L297

Generic question: after recieving feedback where I think I'd like to update the scope of the issue, is it better that I update the initial issue, or that I note that I'm updating the issue in a comment in the thread?

Adding:

• Visualising the delay data as an initial step
• Posterior predictions for a single or both models (this clarifies what I had "extracting posterior distributions" -- still unclear exactly what is being predicted here)

Nice to have / with pseduocode:

• Translating a fitted distribution to a PMF

fter recieving feedback where I think I'd like to update the scope of the issue

I would typically update the initial issue with a note that I have done so and a link to the comment etc that motivated it. Not sure if there is a good practice guide for this but I like it as it makes it easier to find info when coming from a PR

Posterior predictions for a single or both mod

You can plot the fit to the actual data as eval metric. We use this in the @parksw3 paper for the ebola case study I believe

Posterior predictions for a single or both models (this clarifies what I had "extracting posterior distributions" -- still unclear exactly what is being predicted here)

You can plot the fit to the actual data as eval metric. We use this @parksw3 paper for the ebola case study I believe

I feel there are several other ways we can visualize the posterior. In our paper, we show truncated mean vs empirical delay, but other people might prefer to see pdfs and cdfs?