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HDCI  

High Dimensional Confidence Interval Based on Lasso and Bootstrap
View on CRAN: Click here


Download and install HDCI package within the R console
Install from CRAN:
install.packages("HDCI")

Install from Github:
library("remotes")
install_github("cran/HDCI")

Install by package version:
library("remotes")
install_version("HDCI", "1.0-2")



Attach the package and use:
library("HDCI")
Maintained by
Xin Xu
[Scholar Profile | Author Map]
First Published: 2017-06-06
Latest Update: 2017-06-06
Description:
Fits regression models on high dimensional data to estimate coefficients and use bootstrap method to obtain confidence intervals. Choices for regression models are Lasso, Lasso+OLS, Lasso partial ridge, Lasso+OLS partial ridge.
How to cite:
Xin Xu (2017). HDCI: High Dimensional Confidence Interval Based on Lasso and Bootstrap. R package version 1.0-2, https://cran.r-project.org/web/packages/HDCI. Accessed 08 May. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited HDCI R package
View HDCI citation profile
Other R packages that HDCI depends, imports, suggests or enhances
Complete documentation for HDCI
Functions, R codes and Examples using the HDCI R package
Some associated functions: LPR . Lasso . LassoOLS . PartRidge . bootLOPR . bootLPR . bootLasso . bootLassoOLS . ci . escv.glmnet . mls . mypredict . 
Some associated R codes: LPR.R . Lasso.R . LassoOLS.R . PartRidge.R . bootLOPR.R . bootLPR.R . bootLasso.R . bootLassoOLS.R . ci.R . escv.glmnet.R . mls.R . mypredict.R .  Full HDCI package functions and examples
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