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RelimpPCR

Relative Importance PCA Regression

v0.3.0 · Jun 1, 2023 · MIT + file LICENSE

Description

Performs Principal Components Analysis (also known as PCA) dimensionality reduction in the context of a linear regression. In most cases, PCA dimensionality reduction is performed independent of the response variable for a regression. This captures the majority of the variance of the model's predictors, but may not actually be the optimal dimensionality reduction solution for a regression against the response variable. An alternative method, optimized for a regression against the response variable, is to use both PCA and a relative importance measure. This package applies PCA to a given data frame of predictors, and then calculates the relative importance of each PCA factor against the response variable. It outputs ordered factors that are optimized for model fit. By performing dimensionality reduction with this method, an individual can achieve a the same r-squared value as performing just PCA, but with fewer PCA factors. References: Yuri Balasanov (2017) <https://ilykei.com>.

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Maintainer: ‘Michael Hernandez <michael@hernandez.ai>’

No Authors@R field in DESCRIPTION.
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  Authors@R: c(person(given = "Michael",
                      family = "Hernandez",
                      role = c("aut", "cre"),
                      email = "micahel@hernandez.ai"),
               person(given = "Yuri",
                      family = "Balasanov",
                      role = "aut"))
as necessary.
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CRAN incoming feasibility

Maintainer: ‘Michael Hernandez <michael@hernandez.ai>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: c(person(given = "Michael",
                      family = "Hernandez",
                      role = c("aut", "cre"),
                      email = "micahel@hernandez.ai"),
               person(given = "Yuri",
                      family = "Balasanov",
                      role = "aut"))
as necessary.
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NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE r-devel-linux-x86_64-debian-clang

CRAN incoming feasibility

Maintainer: ‘Michael Hernandez <michael@hernandez.ai>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: c(person(given = "Michael",
                      family = "Hernandez",
                      role = c("aut", "cre"),
                      email = "micahel@hernandez.ai"),
               person(given = "Yuri",
                      family = "Balasanov",
                      role = "aut"))
as necessary.
NOTE r-devel-linux-x86_64-debian-gcc

CRAN incoming feasibility

Maintainer: ‘Michael Hernandez <michael@hernandez.ai>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: c(person(given = "Michael",
                      family = "Hernandez",
                      role = c("aut", "cre"),
                      email = "micahel@hernandez.ai"),
               person(given = "Yuri",
                      family = "Balasanov",
                      role = "aut"))
as necessary.

Dependency Network

Dependencies Reverse dependencies relaimpo Rmisc caret ggplot2 reshape2 logger RelimpPCR

Version History

new 0.3.0 Mar 9, 2026