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sRDA  

Sparse Redundancy Analysis
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("sRDA", "1.0.0")



Attach the package and use:
library("sRDA")
Maintained by
Attila Csala
[Scholar Profile | Author Map]
First Published: 2017-12-14
Latest Update: 2017-12-14
Description:
Sparse redundancy analysis for high dimensional (biomedical) data. Directional multivariate analysis to express the maximum variance in the predicted data set by a linear combination of variables of the predictive data set. Implemented in a partial least squares framework, for more details see Csala et al. (2017) <doi:10.1093/bioinformatics/btx374>.
How to cite:
Attila Csala (2017). sRDA: Sparse Redundancy Analysis. R package version 1.0.0, https://cran.r-project.org/web/packages/sRDA. Accessed 03 May. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited sRDA R package
View sRDA citation profile
Other R packages that sRDA depends, imports, suggests or enhances
Complete documentation for sRDA
Functions, R codes and Examples using the sRDA R package
Some associated functions: generate_data . sCCA . sRDA . 
Some associated R codes: generate_data.R . get_cross_validated_penalty_parameters.R . get_enet.R . get_multiple_LVs.R . get_non_parallel_cv.R . get_parallel_cv.R . get_split_sets.R . get_ust.R . sCCA.R . sRDA.R .  Full sRDA package functions and examples
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