Other packages > Find by keyword >

RelimpPCR  

Relative Importance PCA Regression
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("RelimpPCR", "0.3.0")



Attach the package and use:
library("RelimpPCR")
Maintained by
Michael Hernandez
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-10-04
Latest Update: 2023-06-01
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>.
How to cite:
Michael Hernandez (2017). RelimpPCR: Relative Importance PCA Regression. R package version 0.3.0, https://cran.r-project.org/web/packages/RelimpPCR
Previous versions and publish date:
0.2.2 (2017-10-04 19:22), 0.2.3 (2017-10-05 12:33), 0.2.4 (2019-05-02 20:20)
Other packages that cited RelimpPCR R package
View RelimpPCR citation profile
Other R packages that RelimpPCR depends, imports, suggests or enhances
Functions, R codes and Examples using the RelimpPCR R package
Some associated functions: RelimpPCR . RelimpPCR.predict . 
Some associated R codes: RelimpPCR.R . RelimpPCR_Predict.R .  Full RelimpPCR package functions and examples
Downloads during the last 30 days
Get rewarded with contribution points by helping add
Reviews / comments / questions /suggestions ↴↴↴

Today's Hot Picks in Authors and Packages

bulletr  
Algorithms for Matching Bullet Lands
Analyze bullet lands using nonparametric methods. We provide a reading routine for x3p files (see &l ...
Download / Learn more Package Citations See dependency  
Deriv  
Symbolic Differentiation
R-based solution for symbolic differentiation. It admits user-defined function as well as function s ...
Download / Learn more Package Citations See dependency  
nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
lgarch  
Simulation and Estimation of Log-GARCH Models
Simulation and estimation of univariate and multivariate log-GARCH models. The main functions of the ...
Download / Learn more Package Citations See dependency  
buildr  
Organize & Run Build Scripts Comfortably
Working with reproducible reports or any other similar projects often require to run the script that ...
Download / Learn more Package Citations See dependency  

22,086

R Packages

187,731

Dependencies

55,244

Author Associations

22,087

Publication Badges

© Copyright 2022 - present. All right reserved, rpkg.net. Contact Us / Suggestions / Concerns