# hdi v0.1-7

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## High-Dimensional Inference

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

## Functions in hdi

 Name Description hdi-package hdi lasso.cv Select Predictors via (10-fold) Cross-Validation of the Lasso riboflavin Riboflavin data set rXb Generate Data Design Matrix $X$ and Coefficient Vector $\beta$ multi.split Calculate P-values Based on Multi-Splitting Approach plot.clusterGroupBound Plot output of hierarchical testing of groups of variables lasso.firstq Determine the first q Predictors in the Lasso Path lasso.proj P-values based on lasso projection method ridge.proj P-values based on ridge projection method fdr.adjust Function to calculate FDR adjusted p-values glm.pval Function to calculate p-values for a generalized linear model. stability Function to perform stability selection hdi Function to perform inference in high-dimensional (generalized) linear models groupBound Lower bound on the l1-norm of groups of regression variables boot.lasso.proj P-values based on the bootstrapped 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. clusterGroupBound Hierarchical structure group tests in linear model No Results!