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dCUR
View on CRAN: Click
here
Download and install dCUR package within the R console
Install from CRAN:
install.packages("dCUR")
Install from Github:
library("remotes")
install_github("cran/dCUR") Install by package version:
library("remotes")
install_version("dCUR", "1.0.2") Attach the package and use:
library("dCUR")
Maintained by
Cesar Gamboa
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[Scholar Profile | Author Map]
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First Published: 2020-10-08
Latest Update: 2025-09-03
Description:
Dynamic CUR (dCUR) boosts the CUR decomposition (Mahoney MW., Drineas P. (2009) ) varying the k, the number of columns and rows used, and its final purposes to help find the stage, which minimizes the relative error to reduce matrix dimension.
The goal of CUR Decomposition is to give a better interpretation of the matrix decomposition employing proper variable selection in the data matrix, in a way that yields a simplified structure. Its origins come from analysis in genetics.
The goal of this package is to show an alternative to variable selection (columns) or individuals (rows). The idea proposed consists of adjusting the probability distributions to the leverage scores and selecting the best columns and rows that minimize the reconstruction error of the matrix approximation ||A-CUR||. It also includes a method that recalibrates the relative importance of the leverage scores according to an external variable of the user's interest.
How to cite:
Cesar Gamboa (2020). dCUR: Dimension Reduction with Dynamic CUR. R package version 1.0.2, https://cran.r-project.org/web/packages/dCUR. Accessed 07 Oct. 2026.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for dCUR
Functions, R codes and Examples using
the dCUR R package
Some associated functions: AASP . CUR . dCUR . mixture_plots . optimal_stage . relevant_variables_plot . var_exp .
Some associated R codes: CUR.R . dCUR.R . globals.R . mixture_plots.R . optimal_stage.R . package_info.R . relevant_variables_plot.R . var_exp.R . Full dCUR package functions and examples
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