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hdi (version 0.1-6)

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

1,434

Version

0.1-6

License

GPL

Maintainer

Lukas Meier

Last Published

March 21st, 2016

Functions in hdi (0.1-6)

lm.pval

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

glm.pval

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

ridge.proj

P-values based on ridge projection method

stability

Function to perform stability selection

hdi-package

hdi

lm.ci

Function to calculate confidence intervals for ordinary multiple linear regression.

lasso.proj

P-values based on lasso projection method

multi.split

Calculate P-values Based on Multi-Splitting Approach

riboflavin

Riboflavin data set

fdr.adjust

Function to calculate FDR adjusted p-values

hdi

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

lasso.firstq

Determine the first q Predictors in the Lasso Path

lasso.cv

Select Predictors via (10-fold) Cross-Validation of the Lasso

clusterGroupBound

Hierarchical structure group tests in linear model

groupBound

Lower bound on the l1-norm of groups of regression variables

plot.clusterGroupBound

Plot output of hierarchical testing of groups of variables

rXb

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