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nsdr
View on CRAN: Click
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Download and install nsdr package within the R console
Install from CRAN:
install.packages("nsdr")
Install from Github:
library("remotes")
install_github("cran/nsdr")
Install by package version:
library("remotes")
install_version("nsdr", "0.1.1")
Attach the package and use:
library("nsdr")
Maintained by
Kyongwon Kim
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-05-11
Latest Update: 2022-11-28
Description:
Provides tools to implement both unsupervised and supervised nonlinear dimension reduction methods. Principal Component Analysis PCA Sliced Inverse Regression SIR and Sliced Average Variance Estimation SAVE are useful methods to reduce the dimensionality of covariates. However they produce linear combinations of covariates. Kernel PCA generalized SIR and generalized SAVE address this problem by extending the applicability of the dimension reduction problem to nonlinear settings. This package includes a comprehensive algorithm for kernel PCA generalized SIR and generalized SAVE including methods for choosing tuning parameters and some essential functions.
How to cite:
Kyongwon Kim (2021). nsdr: Nonlinear Sufficient Dimension Reduction. R package version 0.1.1, https://cran.r-project.org/web/packages/nsdr
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