Package: HDCI 1.0-2

Xin Xu

HDCI: High Dimensional Confidence Interval Based on Lasso and Bootstrap

Fits regression models on high dimensional data to estimate coefficients and use bootstrap method to obtain confidence intervals. Choices for regression models are Lasso, Lasso+OLS, Lasso partial ridge, Lasso+OLS partial ridge.

Authors:Hanzhong Liu, Xin Xu, Jingyi Jessica Li

HDCI_1.0-2.tar.gz
HDCI_1.0-2.zip(r-4.7)HDCI_1.0-2.zip(r-4.6)HDCI_1.0-2.zip(r-4.5)
HDCI_1.0-2.tgz(r-4.6-any)HDCI_1.0-2.tgz(r-4.5-any)
HDCI_1.0-2.tar.gz(r-4.7-any)HDCI_1.0-2.tar.gz(r-4.6-any)
HDCI_1.0-2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
HDCI/json (API)

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

Bug tracker:https://github.com/cranhaven/cranhaven.r-universe.dev/issues

On CRAN:

Conda:

archivedpackagesr-universe

3.01 score 5 stars 2 packages 34 scripts 215 downloads 1 mentions 12 exports 13 dependencies

Last updated from:50c9b73983 (on package/HDCI). Checks:9 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK191
source / vignettesOK141
linux-release-x86_64OK131
macos-release-arm64OK115
macos-oldrel-arm64OK97
windows-develOK116
windows-releaseOK108
windows-oldrelOK128
wasm-releaseOK133

Exports:bootLassobootLassoOLSbootLOPRbootLPRciescv.glmnetLassoLassoOLSLPRmlsmypredictPartRidge

Dependencies:codetoolsdoParallelforeachglmnetiteratorslatticeMatrixmvtnormRcppRcppEigenshapeslamsurvival