# High-Dimensional Inference

## Documentation for package ‘hdi’ version 0.1-10

- DESCRIPTION file.
- Package NEWS.

## Help Pages

hdi-package | hdi
boot.lasso.proj | P-values based on the bootstrapped lasso projection method
clusterGroupBound | Hierarchical structure group tests in linear model
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 | Select Predictors via (10-fold) Cross-Validation of the Lasso
lasso.firstq | 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 | 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
rX | Generate Data Design Matrix X and Coefficient Vector beta
rXb | Generate Data Design Matrix X and Coefficient Vector beta
stability | Function to perform stability selection