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hdi (version 0.1-9)

High-Dimensional Inference

Description

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

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Version

Install

install.packages('hdi')

Monthly Downloads

1,249

Version

0.1-9

License

GPL

Maintainer

Lukas Meier

Last Published

May 27th, 2021

Functions in hdi (0.1-9)

lasso.proj

P-values based on lasso projection method
hdi

Function to perform inference in high-dimensional (generalized) linear models
fdr.adjust

Function to calculate FDR adjusted p-values
clusterGroupBound

Hierarchical structure group tests in linear model
glm.pval

Function to calculate p-values for a generalized linear model.
hdi-package

hdi
lasso.firstq

Determine the first q Predictors in the Lasso Path
groupBound

Lower bound on the l1-norm of groups of regression variables
lasso.cv

Select Predictors via (10-fold) Cross-Validation of the Lasso
boot.lasso.proj

P-values based on the bootstrapped lasso projection method
lm.pval

Function to calculate p-values for ordinary multiple linear regression.
lm.ci

Function to calculate confidence intervals for ordinary multiple linear regression.
ridge.proj

P-values based on ridge projection method
stability

Function to perform stability selection
rXb

Generate Data Design Matrix \(X\) and Coefficient Vector \(\beta\)
riboflavin

Riboflavin data set
plot.clusterGroupBound

Plot output of hierarchical testing of groups of variables
multi.split

Calculate P-values Based on Multi-Splitting Approach