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.tar.gz(r-4.5-noble)HDtweedie_1.2.tar.gz(r-4.4-noble)
HDtweedie_1.2.tgz(r-4.4-emscripten)HDtweedie_1.2.tgz(r-4.3-emscripten)
HDtweedie.pdf |HDtweedie.html
HDtweedie/json (API)

# Install 'HDtweedie' in R:
install.packages('HDtweedie', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • fortran– Runtime library for GNU Fortran applications
Datasets:
  • auto - A motor insurance dataset

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

4 exports 3 stars 0.61 score 0 dependencies 1 dependents 43 scripts 379 downloads

Last updated 2 years agofrom:608a38f548. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 22 2024
R-4.5-linux-x86_64OKAug 22 2024

Exports:coef.HDtweediecv.HDtweedieHDtweediepredict.HDtweedie

Dependencies: