HTLR
Bayesian Logistic Regression with Heavy-Tailed Priors
v1.0
·
Dec 15, 2025
·
GPL-3
Description
Efficient Bayesian multinomial logistic regression based on heavy-tailed (hyper-LASSO, non-convex) priors. The posterior of coefficients and hyper-parameters is sampled with restricted Gibbs sampling for leveraging the high-dimensionality and Hamiltonian Monte Carlo for handling the high-correlation among coefficients. A detailed description of the method: Li and Yao (2018), Journal of Statistical Computation and Simulation, 88:14, 2827-2851, <doi:10.48550/arXiv.1405.3319>.
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| r-devel-linux-x86_64-debian-clang | OK |
| r-devel-linux-x86_64-debian-gcc | OK |
| r-devel-linux-x86_64-fedora-clang | OK |
| r-devel-linux-x86_64-fedora-gcc | OK |
| r-devel-macos-arm64 | OK |
| r-devel-windows-x86_64 | OK |
| r-oldrel-macos-arm64 | NOTE |
| r-oldrel-macos-x86_64 | NOTE |
| r-oldrel-windows-x86_64 | OK |
| r-patched-linux-x86_64 | OK |
| r-release-linux-x86_64 | OK |
| r-release-macos-arm64 | OK |
| r-release-macos-x86_64 | OK |
| r-release-windows-x86_64 | OK |
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NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
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r-oldrel-macos-arm64
installed package size
installed size is 5.8Mb
sub-directories of 1Mb or more:
doc 1.0Mb
libs 3.6Mb
NOTE
r-oldrel-macos-x86_64
installed package size
installed size is 5.9Mb
sub-directories of 1Mb or more:
doc 1.0Mb
libs 3.7Mb
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1.0
Mar 9, 2026