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SparseBiplots

'HJ-Biplot' using Different Ways of Penalization Plotting with 'ggplot2'

The 'HJ-Biplot' is a multivariate method that represents high-dimensional data in a low-dimensional subspace, capturing most of the information’s variability in just a few dimensions. This package implements three new regularized versions of the HJ-Biplot: Ridge, LASSO, and Elastic Net. These versions introduce restrictions that shrink or zero-out variable weights to improve interpretability based on regularization theory. All methods provide graphical representations using 'ggplot2'.

Versions across snapshots

VersionRepositoryFileSize
4.1.1 rolling linux/jammy R-4.5 SparseBiplots_4.1.1.tar.gz 47.7 KiB
4.1.1 rolling linux/noble R-4.5 SparseBiplots_4.1.1.tar.gz 47.7 KiB
4.1.1 rolling source/ R- SparseBiplots_4.1.1.tar.gz 11.6 KiB
4.1.1 latest linux/jammy R-4.5 SparseBiplots_4.1.1.tar.gz 47.7 KiB
4.1.1 latest linux/noble R-4.5 SparseBiplots_4.1.1.tar.gz 47.7 KiB
4.1.1 latest source/ R- SparseBiplots_4.1.1.tar.gz 11.6 KiB
4.1.1 2026-04-26 source/ R- SparseBiplots_4.1.1.tar.gz 11.6 KiB
4.1.1 2026-04-23 source/ R- SparseBiplots_4.1.1.tar.gz 11.6 KiB
4.1.1 2026-04-09 windows/windows R-4.5 SparseBiplots_4.1.1.zip 50.8 KiB
4.0.1 2025-04-20 source/ R- SparseBiplots_4.0.1.tar.gz 10.4 KiB

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