High-Dimensional Inference

Documentation for package ‘hdi’ version 0.0-6

hdi-package	hdi
clusterLowerBound	Group test of variable importance in a high-dimensional linear model, using a hierarchical structure.
fdr.adjust	Function to calculate FDR adjusted p-values
glm.pval	Function to calculate p-values for a generalized linear model.
groupLowerBound	Lower bound on the l1-norm of groups of regression variables
hdi	Function to perform inference in high-dimensional (generalized) linear models
lasso.cv	Function to select predictors based on 10-fold cross-validation of the lasso estimator.
lasso.firstq	Function to determine the first q predictors in the lasso path.
lm.pval	Function to calculate p-values for ordinary multiple linear regression.
multi.split	Function to calculate p-values based on multi-splitting approach
plot.clusterLowerBound	Plot output of hierarchical testing of groups of variables
riboflavin	Riboflavin data set
stability	Function to perform stability selection