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LRQVB

Low Rank Correction Quantile Variational Bayesian Algorithm for Multi-Source Heterogeneous Models

v1.0.0 · Oct 25, 2025 · MIT + file LICENSE

Description

A Low Rank Correction Variational Bayesian algorithm for high-dimensional multi-source heterogeneous quantile linear models. More details have been written up in a paper submitted to the journal Statistics in Medicine, and the details of variational Bayesian methods can be found in Ray and Szabo (2021) <doi:10.1080/01621459.2020.1847121>. It simultaneously performs parameter estimation and variable selection. The algorithm supports two model settings: (1) local models, where variable selection is only applied to homogeneous coefficients, and (2) global models, where variable selection is also performed on heterogeneous coefficients. Two forms of parameter estimation are output: one is the standard variational Bayesian estimation, and the other is the variational Bayesian estimation corrected with low-rank adjustment.

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  installed size is  5.2Mb
  sub-directories of 1Mb or more:
    libs   5.0Mb
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installed package size

  installed size is  5.2Mb
  sub-directories of 1Mb or more:
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NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE r-oldrel-macos-arm64

installed package size

  installed size is  5.2Mb
  sub-directories of 1Mb or more:
    libs   5.0Mb
NOTE r-oldrel-macos-x86_64

installed package size

  installed size is  5.2Mb
  sub-directories of 1Mb or more:
    libs   5.1Mb

Dependency Network

Dependencies Reverse dependencies Rcpp glmnet lava MASS LRQVB

Version History

new 1.0.0 Mar 9, 2026