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hdi (version 0.1-6)
High-Dimensional Inference
Description
Implementation of multiple approaches to perform inference in high-dimensional models.
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0.0-6
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Install
install.packages('hdi')
Monthly Downloads
1,150
Version
0.1-6
License
GPL
Maintainer
Lukas Meier
Last Published
March 21st, 2016
Functions in hdi (0.1-6)
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lm.pval
Function to calculate p-values for ordinary multiple linear regression.
glm.pval
Function to calculate p-values for a generalized linear model.
ridge.proj
P-values based on ridge projection method
stability
Function to perform stability selection
hdi-package
hdi
lm.ci
Function to calculate confidence intervals for ordinary multiple linear regression.
lasso.proj
P-values based on lasso projection method
multi.split
Calculate P-values Based on Multi-Splitting Approach
riboflavin
Riboflavin data set
fdr.adjust
Function to calculate FDR adjusted p-values
hdi
Function to perform inference in high-dimensional (generalized) linear models
lasso.firstq
Determine the first q Predictors in the Lasso Path
lasso.cv
Select Predictors via (10-fold) Cross-Validation of the Lasso
clusterGroupBound
Hierarchical structure group tests in linear model
groupBound
Lower bound on the l1-norm of groups of regression variables
plot.clusterGroupBound
Plot output of hierarchical testing of groups of variables
rXb
Generate Data Design Matrix \(X\) and Coefficient Vector \(\beta\)