Hacktoberfest 2026: the issues maintainers tagged for October, open and beginner-friendly. Browse Hacktoberfest issues

Inferring causal impact using Bayesian structural time-series models

Open
#52 0 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Assessment

Difficulty
3/5
Estimated time
1-2 days
Newbie friendliness
20/100
Issue type
Documentation
Clarity
Needs clarification
Activity status
Stale
Tech stack
machine-learning
Domain
content

Research direction

Start with the linked Project Euclid paper and inspect the repository’s existing TIL entries to determine the intended format and placement. The issue does not name a file, entry point, or specific change; completion would need to be defined as a published TIL entry explaining this topic in the project’s established style.

Written by the indexing model from the issue text.

Description

To Read
Dominant language
CSS
Stars
8
Forks
2
PR merge metrics
No merged PRs in 30d

Getting set up

This project ships no dev container, Dockerfile or contributing guide, so setting up is up to you: start from its README, and see our first-contribution guide for the general steps.

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

More from Julian/til

All issues in Julian/til

Similar issues

More Content issues

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.