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glmpermu

0.0.1

Permutation-Based Inference for Generalized Linear Models

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2Kdownloads / year
test coverage
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Overview

About
Maintained by Xuekui ZhangFirst published 2024-03-121 releasesCRAN page ↗

In practical applications, the assumptions underlying generalized linear models frequently face violations, including incorrect specifications of the outcome variable's distribution or omitted predictors. These deviations can render the results of standard generalized linear models unreliable. As the sample size increases, what might initially appear as minor issues can escalate to critical concerns. To address these challenges, we adopt a permutation-based inference method tailored for generalized linear models. This approach offers robust estimations that effectively counteract the mentioned problems, and its effectiveness remains consistent regardless of the sample size.

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Health

CRAN checks
1NOTE12OK
Failing flavors
  • NOTE r-devel-linux-x86_64-debian-gcc
Slowest check: 44 s · r-devel-linux-x86_64-fedora-clang
Code health
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Tests · ratio 0.00
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Coverage
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Documentation · exports
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Check history
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
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Code & Tests

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People (4)
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Package Timeline

1 release. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 0.0.1Latest
    2026-03-10 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2024-03-12
Total releases
1 / 2 yrs
License
MIT + file LICENSE OSI
Download size
3.6 KB
Installed size
not tracked yet
With dependencies
not tracked yet
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