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qgam

Smooth Additive Quantile Regression Models

v2.0.0 · Apr 10, 2025 · GPL (>= 2)

Description

Smooth additive quantile regression models, fitted using the methods of Fasiolo et al. (2020) <doi:10.1080/01621459.2020.1725521>. See Fasiolo at al. (2021) <doi:10.18637/jss.v100.i09> for an introduction to the package. Differently from 'quantreg', the smoothing parameters are estimated automatically by marginal loss minimization, while the regression coefficients are estimated using either PIRLS or Newton algorithm. The learning rate is determined so that the Bayesian credible intervals of the estimated effects have approximately the correct coverage. The main function is qgam() which is similar to gam() in 'mgcv', but fits non-parametric quantile regression models.

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r-devel-macos-arm64 OK
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r-release-windows-x86_64 OK
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NOTE r-oldrel-macos-arm64

installed package size

  installed size is  6.0Mb
  sub-directories of 1Mb or more:
    doc   5.2Mb
NOTE r-oldrel-macos-x86_64

installed package size

  installed size is  6.0Mb
  sub-directories of 1Mb or more:
    doc   5.2Mb
NOTE r-oldrel-windows-x86_64

installed package size

  installed size is  5.9Mb
  sub-directories of 1Mb or more:
    doc   5.2Mb
OK r-patched-linux-x86_64

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OK r-release-linux-x86_64

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OK r-release-macos-arm64

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OK r-release-windows-x86_64

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Check History

NOTE 11 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE r-oldrel-macos-arm64

installed package size

  installed size is  6.0Mb
  sub-directories of 1Mb or more:
    doc   5.2Mb
NOTE r-oldrel-macos-x86_64

installed package size

  installed size is  6.0Mb
  sub-directories of 1Mb or more:
    doc   5.2Mb
NOTE r-oldrel-windows-x86_64

installed package size

  installed size is  5.9Mb
  sub-directories of 1Mb or more:
    doc   5.2Mb

Reverse Dependencies (7)

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Dependency Network

Dependencies Reverse dependencies mgcv shiny plyr doParallel mgcViz DHARMa abtest curvir sjSDM DAAG ctsem qgam

Version History

new 2.0.0 Mar 9, 2026