Package: HDtweedie 1.2

Wei Qian

HDtweedie: The Lasso for Tweedie's Compound Poisson Model Using an IRLS-BMD Algorithm

The Tweedie lasso model implements an iteratively reweighed least square (IRLS) strategy that incorporates a blockwise majorization decent (BMD) method, for efficiently computing solution paths of the (grouped) lasso and the (grouped) elastic net methods.

Authors:Wei Qian <[email protected]>, Yi Yang <[email protected]>, Hui Zou <[email protected]>

HDtweedie_1.2.tar.gz
HDtweedie_1.2.zip(r-4.7-x86_64)HDtweedie_1.2.zip(r-4.7-arm64)HDtweedie_1.2.zip(r-4.6-x86_64)HDtweedie_1.2.zip(r-4.6-arm64)
HDtweedie_1.2.tar.gz(r-4.7-arm64)HDtweedie_1.2.tar.gz(r-4.7-x86_64)HDtweedie_1.2.tar.gz(r-4.6-arm64)HDtweedie_1.2.tar.gz(r-4.6-x86_64)
HDtweedie_1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
HDtweedie/json (API)

# Install 'HDtweedie' in R:
install.packages('HDtweedie', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • fortran– Runtime library for GNU Fortran applications
Datasets:
  • auto - A motor insurance dataset

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblasfortranglibc

2.49 score 3 stars 1 packages 34 scripts 315 downloads 4 exports 0 dependencies

Last updated from:608a38f548. Checks:9 OK, 1 WARNING. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK86
linux-devel-x86_64OK96
source / vignettesOK155
linux-release-arm64OK81
linux-release-x86_64OK90
windows-devel-arm64OK174
windows-devel-x86_64OK121
windows-release-arm64WARNING198
windows-release-x86_64OK95
wasm-releaseOK69

Exports:coef.HDtweediecv.HDtweedieHDtweediepredict.HDtweedie

Dependencies: