High-Dimensional Inference
Implementation of multiple approaches to perform inference in high-dimensional models.
P-values based on the bootstrapped lasso projection method
Hierarchical structure group tests in linear model
Function to calculate FDR adjusted p-values
Function to calculate p-values for a generalized linear model.
Lower bound on the l1-norm of groups of regression variables
Function to perform inference in high-dimensional (generalized) linear models
hdi
Select Predictors via (10-fold) Cross-Validation of the Lasso
Determine the first q Predictors in the Lasso Path
P-values based on lasso projection method
Function to calculate confidence intervals for ordinary multiple linear regression.
Function to calculate p-values for ordinary multiple linear regression.
Calculate P-values Based on Multi-Splitting Approach
Plot output of hierarchical testing of groups of variables
Generate Data Design Matrix X and Coefficient Vector β
Riboflavin data set
P-values based on ridge projection method
Function to perform stability selection
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