Package: hdi 0.1-10

hdi: High-Dimensional Inference

Implementation of multiple approaches to perform inference in high-dimensional models.

Authors:Lukas Meier [aut, cre], Ruben Dezeure [aut], Nicolai Meinshausen [aut], Martin Maechler [aut], Peter Buehlmann [aut]

# Install 'hdi' in R:

install.packages('hdi', repos = c('https://meierluk.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

On CRAN:

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

Last updated from:3eb71fb52b. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	164
source / vignettes	OK	168
linux-release-x86_64	OK	164
macos-release-arm64	OK	213
macos-oldrel-arm64	OK	219
windows-devel	OK	166
windows-release	OK	138
windows-oldrel	OK	130
wasm-release	OK	94

Help page	Topics
hdi	hdi-package
P-values based on the bootstrapped lasso projection method	boot.lasso.proj
Hierarchical structure group tests in linear model	clusterGroupBound
Function to calculate FDR adjusted p-values	fdr.adjust
Function to calculate p-values for a generalized linear model.	glm.pval
Lower bound on the l1-norm of groups of regression variables	groupBound
Function to perform inference in high-dimensional (generalized) linear models	hdi
Select Predictors via (10-fold) Cross-Validation of the Lasso	lasso.cv
Determine the first q Predictors in the Lasso Path	lasso.firstq
P-values based on lasso projection method	lasso.proj
Function to calculate confidence intervals for ordinary multiple linear regression.	lm.ci
Function to calculate p-values for ordinary multiple linear regression.	lm.pval
Calculate P-values Based on Multi-Splitting Approach	multi.split
Plot output of hierarchical testing of groups of variables	plot.clusterGroupBound
Riboflavin data set	riboflavin
P-values based on ridge projection method	ridge.proj
Generate Data Design Matrix X and Coefficient Vector beta	rX rXb
Function to perform stability selection	stability