statsmodels / statsmodels/statsmodels
Multiple Imputation
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
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- Forks
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- Avg merge
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- Merged PRs (30d)
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Description
Add intelligent way of dealing with missing data. For example, multiple imputation. Currently both R and Stata offer this.
See for example:
- http://sites.stat.psu.edu/~jls/mifaq.html
- http://www.stata.com/manuals13/mi.pdf
- http://r.iq.harvard.edu/docs/amelia/amelia.pdf
- http://www.stat.ucla.edu/~yajima/Publication/mipaper.rev04.pdf
A general overview on dealing with missing data: http://www.uvm.edu/~dhowell/StatPages/More_Stuff/Missing_Data/Missing.html
Does something like this belong in statsmodels or in scikit learn? Scikit currently has an imputer but it is very rudimentary (mean filling).
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue names no files, tests, or entry point. Start by reviewing the linked multiple-imputation references and deciding whether the work belongs in statsmodels or scikit-learn; the scope and completion criteria still need to be defined.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100