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missForest

missForest is a nonparametric, mixed-type imputation method for basically any type of data for the statistical software R.

https://github.com/stekhoven/missforest

Science Score: 23.0%

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    Found 1 DOI reference(s) in README
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    2 of 6 committers (33.3%) from academic institutions
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    Low similarity (8.0%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

missForest is a nonparametric, mixed-type imputation method for basically any type of data for the statistical software R.

Basic Info
Statistics
  • Stars: 99
  • Watchers: 7
  • Forks: 24
  • Open Issues: 12
  • Releases: 0
Created over 13 years ago · Last pushed almost 3 years ago
Metadata Files
Readme

README.md

missForest

missForest is a nonparametric, mixed-type imputation method for basically any type of data.
Here, we host the R-package "missForest" for the statistical software R.

The method is based on the publication Stekhoven and Bühlmann, 2012. The R package contains a vignette on how to use "missForest" in R including many helpful examples.

Upcoming

Currently, we are working on going multiple imputation with missForest. We are testing several ways of doing it, including an implicit approach making multiple full data set imputations potentially unnecessary. We expect to see these first extensions in the second half of 2019.

Deal with tibbles and variable attributes.

Potential innovations alongside:

  • storage of missForests (if this is feasible, it could be used for predictions)
  • housekeeping the code for efficiency and safety

For later...

Stuff we consider less interesting - write us if you disagree:

  • different stopping criteria (missForest is very well performing on the existing criterion, we see no need to adjust for this)
  • random seed tracking/setting for fully reproducible imputation results (due to the little variability in the estimation of missForest - even if it is stochastic - results are quasi reproducible)
  • computation time estimation (harder than we thought and not so pressing)

Contact us

Contact me by email: stekhoven@nexus.ethz.ch

References: Stekhoven, D.J. and Buehlmann, P. (2012), 'MissForest - nonparametric missing value imputation for mixed-type data', Bioinformatics, 28(1) 2012, 112-118, doi: 10.1093/bioinformatics/btr597

Owner

  • Name: Daniel Stekhoven
  • Login: stekhoven
  • Kind: user
  • Location: Switzerland
  • Company: ETH - NEXUS Personalized Health Technologies

GitHub Events

Total
  • Watch event: 8
  • Issue comment event: 1
  • Fork event: 1
Last Year
  • Watch event: 8
  • Issue comment event: 1
  • Fork event: 1

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 58
  • Total Committers: 6
  • Avg Commits per committer: 9.667
  • Development Distribution Score (DDS): 0.672
Past Year
  • Commits: 2
  • Committers: 1
  • Avg Commits per committer: 2.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Daniel Stekhoven d****n@s****h 19
Daniel Stekhoven s****n@n****h 16
Daniel Stekhoven s****n@g****m 9
Yang (Simon) Guo 3****v 6
jasenfinch j****9@a****k 6
kevin k****n@B****d 2
Committer Domains (Top 20 + Academic)
bsus-mbp.broadband: 1 aber.ac.uk: 1 nexus.ethz.ch: 1 scqm.ch: 1

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 33
  • Total pull requests: 4
  • Average time to close issues: almost 2 years
  • Average time to close pull requests: 9 months
  • Total issue authors: 26
  • Total pull request authors: 3
  • Average comments per issue: 1.48
  • Average comments per pull request: 0.25
  • Merged pull requests: 3
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • stekhoven (3)
  • ivan-marroquin (2)
  • Apprentice2 (2)
  • stephematician (2)
  • pablo14 (2)
  • HedvigS (2)
  • rkb965 (1)
  • 2902 (1)
  • dashaub (1)
  • Mosen111 (1)
  • markvanderloo (1)
  • joundso (1)
  • A-Pai (1)
  • CosentinoF (1)
  • whoiskeren (1)
Pull Request Authors
  • jasenfinch (2)
  • kkmann (1)
  • sgyzetrov (1)
Top Labels
Issue Labels
enhancement (7) consider (3) question (3) type bug (2) bug (2)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 6,491 last-month
  • Total docker downloads: 46,722
  • Total dependent packages: 20
  • Total dependent repositories: 48
  • Total versions: 7
  • Total maintainers: 1
cran.r-project.org: missForest

Nonparametric Missing Value Imputation using Random Forest

  • Versions: 7
  • Dependent Packages: 20
  • Dependent Repositories: 48
  • Downloads: 6,491 Last month
  • Docker Downloads: 46,722
Rankings
Forks count: 3.3%
Dependent packages count: 3.3%
Dependent repos count: 3.6%
Downloads: 4.4%
Stargazers count: 4.7%
Average: 7.0%
Docker downloads count: 22.7%
Maintainers (1)
stekhoven@stat.math.ethz.ch
Last synced: 11 months ago

Dependencies

DESCRIPTION cran
  • doRNG * imports
  • foreach * imports
  • iterators * imports
  • itertools * imports
  • randomForest * imports
  • doParallel * suggests