pymc-devs / pymc-devs/pymc-examples

Hurricane Path Forecasts using HSGP and Vector Auto Regression

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proposal
Dominant language
Python
Stars
398
Forks
325
Avg merge
9d 15m
Merged PRs (30d)
1

Description

Notebook proposal

Title: Hurricane Path Forecasts

Why should this notebook be added to pymc-examples?

I think this would be an interesting example to have because of the following:

  • This model is a multi-output estimation (distance + direction) problem
  • It is a relevant topic with real world implications that are currently newsworthy
  • It shows how one can apply/extend the very cool work depicted in example_1 by @NathanielF and in example_2 by @ricardoV94

Suggested categories:

  • Level: Beginner/Intermediate

Related notebooks

Links to related notebooks mentioned above.

References

references in notebooks above + any other if relevant at completion of example.

Preliminary work

I have a good chunk of the work complete but it is still a work in progress. I am trying to gauge if this will be of interest to the PYMC community. here is a link to what I have so far.

Contributor guide

Open the contributing guide

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.

Research direction

Start by reviewing the preliminary work in the linked gist and the related bayesian_var_model example, along with the referenced Bayesian vector autoregression post. Confirm the proposed hurricane path model, data, and references, then prepare a complete example notebook for pymc-examples with the stated beginner/intermediate scope.

Written by the indexing model from the issue text.

Assessment

Tech stack
jupyter-notebook, python
Domain
machine-learning
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
32/100

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