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
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Type Package
Date 2019-03-27
DependsNote scalreg does not correctly import lars etc, so we need to depend on it
SuggestsNote for tests only
Encoding UTF-8
License GPL
Repository CRAN
Repository/R-Forge/Project hdi
Repository/R-Forge/Revision 155
Repository/R-Forge/DateTimeStamp 2019-03-29 09:03:20
Date/Publication 2019-03-29 10:50:03 UTC
NeedsCompilation no
Packaged 2019-03-29 09:10:52 UTC; rforge

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