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HCTR
View on CRAN: Click
here
Download and install HCTR package within the R console
Install from CRAN:
install.packages("HCTR")
Install from Github:
library("remotes")
install_github("cran/HCTR")
Install by package version:
library("remotes")
install_version("HCTR", "0.1.1")
Attach the package and use:
library("HCTR")
Maintained by
Tao Jiang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-10-07
Latest Update: 2019-11-22
Description:
A novel searching scheme for tuning parameter in high-dimensional
penalized regression. We propose a new estimate of the regularization
parameter based on an estimated lower bound of the proportion of false
null hypotheses (Meinshausen and Rice (2006) ).
The bound is estimated by applying the empirical null distribution of the higher
criticism statistic, a second-level significance testing, which is constructed
by dependent p-values from a multi-split regression and aggregation method
(Jeng, Zhang and Tzeng (2019) ). An estimate
of tuning parameter in penalized regression is decided corresponding to the lower
bound of the proportion of false null hypotheses. Different penalized
regression methods are provided in the multi-split algorithm.
How to cite:
Tao Jiang (2019). HCTR: Higher Criticism Tuned Regression. R package version 0.1.1, https://cran.r-project.org/web/packages/HCTR. Accessed 06 May. 2025.
Previous versions and publish date:
0.1.0 (2019-10-07 16:30)
Other packages that cited HCTR R package
View HCTR citation profile
Other R packages that HCTR depends,
imports, suggests or enhances
Complete documentation for HCTR
Functions, R codes and Examples using
the HCTR R package
Some associated functions: bounding.seq . est.lambda . est.prop . final.selection . highdim.p . multi.adlasso . multi.lasso . multi.mcp . multi.scad . pmpv .
Some associated R codes: bounding.seq.R . est.lambda.R . est.prop.R . final.selection.R . highdim.p.R . multi.adlasso.R . multi.lasso.R . multi.mcp.R . multi.scad.R . pmpv.R . Full HCTR package functions and examples
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