statsmodels / statsmodels/statsmodels
diagnostic tests - compared to R
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Description
two links that provide summaries of R functions for model diagnostics
http://www.statmethods.net/stats/rdiagnostics.html
http://rstudio-pubs-static.s3.amazonaws.com/2134_a31c4c71a01c472eb6081432e80689b2.html
We have essentially everything, except *), and more
ncvTest is just Breush-Pagan http://www.inside-r.org/node/86862
*) missing:
- Global Validation of Linear Model Assumptions http://www.jstor.org/stable/30047462
never heard of this one, but might be a useful addition - ceresplots whatever they are http://www.inside-r.org/packages/cran/car/docs/ceresPlots
some diagnostics are extended to GLM
need to check what we can generalize or use for other models
possibility: use R examples to improve documentation for our functions
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
Start by reviewing the two linked R diagnostics summaries and the listed references, then compare them with the existing statsmodels diagnostics. Inventory which diagnostics are missing, including Global Validation of Linear Model Assumptions and ceresPlots, and determine what can generalize to GLM or other models; done means a decided scope with corresponding functionality or documentation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, r
- Domain
- analytics, data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100