From 1fb9c333cb836bb114d760a83bddefc9460730ee Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" <41898282+github-actions[bot]@users.noreply.github.com> Date: Tue, 27 Aug 2024 19:23:00 +0100 Subject: [PATCH] Automatic README update (#754) Co-authored-by: github-merge-queue[bot] <118344674+github-merge-queue[bot]@users.noreply.github.com> --- README.md | 20 ++++++++++++++++++++ 1 file changed, 20 insertions(+) diff --git a/README.md b/README.md index 1f86d6207..d21b2dcde 100644 --- a/README.md +++ b/README.md @@ -90,6 +90,20 @@ cost of the granularity of estimates or real-time performance, include: - Adjustment for the remaining susceptible population beyond the forecast horizon. +By default, all these models are fit with [MCMC +sampling](https://mc-stan.org/docs/reference-manual/mcmc.html) using the +[`rstan`](https://mc-stan.org/users/interfaces/rstan) R package as the +backend. Users can, however, switch to use approximate algorithms like +[variational +inference](https://en.wikipedia.org/wiki/Variational_Bayesian_methods), +the +[pathfinder](https://mc-stan.org/docs/reference-manual/pathfinder.html) +algorithm, or [Laplace +approximation](https://mc-stan.org/docs/reference-manual/laplace.html) +especially for quick prototyping. The latter two methods are provided +through the [`cmdstanr`](https://mc-stan.org/cmdstanr/) R package, so +users will have to install that separately. + The documentation for `estimate_infections` provides examples of the implementation of the different options available. @@ -175,6 +189,12 @@ the two main functions in the package and how to set up them up. It also discusses how to summarise and visualise the results after running the models. +More broadly, users can also learn the details of estimating delay +distributions, nowcasting, and forecasting in a structured way through +the free and open short-course, [“Nowcasting and forecasting infectious +disease dynamics”](https://nfidd.github.io/nfidd/), developed by some +authors of this package. +