SUM KDE followup

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#2,715 2 comments 0 reactions 0 assignees View on GitHub

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Assessment

Difficulty
5/5
Estimated time
Over a week
Newbie friendliness
20/100
Issue type
Feature
Clarity
Needs clarification
Activity status
Stale
Tech stack
python
Domain
data

Research direction

Start by reviewing issue #2318 and the referenced pull request #1271 files, then compare the new KDE implementation with the old multivariate KDE. Investigate the listed needs for kernel bandwidth constants, result caching, grid/interpolation support, and conditional estimation; done would require a decided scope and corresponding tests for the selected additions.

Written by the indexing model from the issue text.

Description

comp-nonparametric

some extra issues while reviewing #2318

  • normal reference for Scott/Silverman with non-gaussian kernel as in https://github.com/statsmodels/statsmodels/pull/1271/files i.e. for Epanechnikov
  • additional kernel constants are in old version (useful for plugin, standard errors, ... ?)
  • Results class with caching, Grid/Interpolation distribution. but evaluation of points in #2318 looks already fast
  • the old multivariate kde has conditional which is still missing in the new version
Dominant language
Python
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Forks
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Avg merge
7h 37m
Merged PRs (30d)
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  4. Open a pull request that references the issue number.

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