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BMA

R package for Bayesian model averaging

https://github.com/hanase/bma

Science Score: 36.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    1 of 1 committers (100.0%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (9.4%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

R package for Bayesian model averaging

Basic Info
  • Host: GitHub
  • Owner: hanase
  • Language: R
  • Default Branch: master
  • Homepage:
  • Size: 138 KB
Statistics
  • Stars: 40
  • Watchers: 3
  • Forks: 13
  • Open Issues: 2
  • Releases: 0
Created over 10 years ago · Last pushed over 1 year ago
Metadata Files
Readme Changelog

README.md

BMA

R build status

R package for Bayesian model averaging and variable selection for linear models, generalized linear models and survival models (cox regression).

Bayesian Model Averaging

Written by Chris Volinsky

Bayesian Model Averaging is a technique designed to help account for the uncertainty inherent in the model selection process, something which traditional statistical analysis often neglects. By averaging over many different competing models, BMA incorporates model uncertainty into conclusions about parameters and prediction. BMA has been applied successfully to many statistical model classes including linear regression, generalized linear models, Cox regression models, and discrete graphical models, in all cases improving predictive performance. Details on these applications can be found in the papers below.

Resources

Statistical Literature

Econometrics Literature

Model combination has been discussed extensively in the econometric literature, usually in the context of combining several experts' forecasts. Bates and Granger (1969) is the forerunner, inspiring a flurry of activity in the field in the early 1970's.

  • "The combination of forecasts". J.M. Bates and C.W.J. Granger (1969). Operations Research Aquarterly, 20, 451-468. [A seminal paper on combining forecasts, inspiring a flurry of activity in the field]

  • "Bayesian and non-Bayesian Methods for Combining Models and Forecasts with Applications to Forecasting International Growth Rates". C. Min and A. Zellner (1993). J. of Econometrics, 56, 89-118.

  • "To Combine or not to Combine? Issues of Combining Forecasts". F.C. Palm and A. Zellner (1992) J. of Forecasting, 11, 687-701.

  • "Experience with forecasting univariate time series and the combination of forecasts (with discussion)". P. Newbold and C.W.J. Granger (1974). Journal of the Royal Statistical Society A, 137, 131-149. [Reading in front of RSS. Comments from statisticians are interesting, and mostly negative toward the idea of combining models.]

Owner

  • Name: Hana Sevcikova
  • Login: hanase
  • Kind: user
  • Location: Seattle
  • Company: @PPgp, @psrc

GitHub Events

Total
  • Issues event: 2
  • Watch event: 2
  • Issue comment event: 1
  • Push event: 13
  • Pull request review event: 1
  • Pull request event: 2
  • Fork event: 2
Last Year
  • Issues event: 2
  • Watch event: 2
  • Issue comment event: 1
  • Push event: 13
  • Pull request review event: 1
  • Pull request event: 2
  • Fork event: 2

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 28
  • Total Committers: 1
  • Avg Commits per committer: 28.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Hana Sevcikova h****s@u****u 28
Committer Domains (Top 20 + Academic)
uw.edu: 1

Issues and Pull Requests

Last synced: 10 months ago

All Time
  • Total issues: 6
  • Total pull requests: 3
  • Average time to close issues: about 1 year
  • Average time to close pull requests: 1 day
  • Total issue authors: 3
  • Total pull request authors: 2
  • Average comments per issue: 0.83
  • Average comments per pull request: 0.67
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 2
  • Pull requests: 2
  • Average time to close issues: 11 days
  • Average time to close pull requests: 1 day
  • Issue authors: 1
  • Pull request authors: 1
  • Average comments per issue: 0.5
  • Average comments per pull request: 0.5
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • Deleetdk (2)
  • hanase (2)
  • dududurant (2)
Pull Request Authors
  • eddelbuettel (2)
  • sbgraves237 (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 6,031 last-month
  • Total docker downloads: 43,434
  • Total dependent packages: 5
  • Total dependent repositories: 10
  • Total versions: 35
  • Total maintainers: 1
cran.r-project.org: BMA

Bayesian Model Averaging

  • Versions: 35
  • Dependent Packages: 5
  • Dependent Repositories: 10
  • Downloads: 6,031 Last month
  • Docker Downloads: 43,434
Rankings
Docker downloads count: 0.6%
Downloads: 5.3%
Forks count: 5.8%
Average: 6.4%
Dependent packages count: 8.1%
Stargazers count: 9.2%
Dependent repos count: 9.2%
Maintainers (1)
hanas@uw.edu
Last synced: 10 months ago

Dependencies

.github/workflows/check-standard.yaml actions
  • actions/cache v2 composite
  • actions/checkout v2 composite
  • actions/upload-artifact main composite
  • r-lib/actions/setup-pandoc v1 composite
  • r-lib/actions/setup-r v1 composite
DESCRIPTION cran
  • inline * depends
  • leaps * depends
  • robustbase * depends
  • rrcov * depends
  • survival * depends
  • methods * imports
  • MASS * suggests