High-Dimensional Inference

Documentation for package ‘hdi’ version 0.1-2

hdi-package	hdi
clusterGroupBound	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.
groupBound	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.
lasso.proj	P-values based on lasso projection method
lm.ci	Function to calculate confidence intervals for ordinary multiple linear regression.
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.clusterGroupBound	Plot output of hierarchical testing of groups of variables
riboflavin	Riboflavin data set
ridge.proj	P-values based on ridge projection method
stability	Function to perform stability selection