## EpiNow2

Estimate Realtime Case Counts and Time-varying Epidemiological Parameters (by epiforecasts)

## bayesian

Bindings for Bayesian TidyModels (by hsbadr)

EpiNow2 | bayesian | |
---|---|---|

1 | 1 | |

112 | 44 | |

0.9% | - | |

9.3 | 7.7 | |

4 days ago | 11 days ago | |

R | R | |

GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |

The number of

For example, an activity of

**mentions**indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.**Stars**- the number of stars that a project has on GitHub.**Growth**- month over month growth in stars.**Activity**is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.For example, an activity of

**9.0**indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.## EpiNow2

Posts with mentions or

**reviews of EpiNow2**. We have used some of these posts to build our list of alternatives and similar projects.-
Reproduction numbers for the third wave
Someone asked for reproduction numbers for Nova Scotia right now so I thought I'd post some generated with the EpiNow2 package. Some explanation is probably required.

## bayesian

Posts with mentions or

**reviews of bayesian**. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-03-17.-
How do you train a Bayesian model
There's MLMod and Bayesian which are TidyModels wrappers for stan_glm and brms (brms is my go to) but I haven't seen anything that indicates how to tune them.

## What are some alternatives?

When comparing EpiNow2 and bayesian you can also consider the following projects:

**GreenPass-Experiments**
- It's possible to create a valid and fake green pass? The scope of this project is try to create one.

**multilevelmod**
- Parsnip wrappers for mixed-level and hierarchical models

**brms**
- brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan