/mfa

An R package for multiple factor analysis

Primary LanguageR

Multiple Factor Analysis (MFA)

What is MFA?

  • Popular factorial method to study sets of variables that are collected on the same set of observations
  • Generalization of principal component analysis
  • Provides factor loadings to indicate the impact of variables on components
  • Factor scores (component scores in PCA) are returned to explain the effect of each observation on the factors
  • Analysis provides a means of quantifying a level of agreement or disagreement between sets of variables

Installation

  1. Install devtools if its not already installed. This can be done through CRAN:
install.packages("devtools")
  1. Load the devtools package:
library(devtools)
  1. Install from the github repository:
install_github("oreluk/MFA")

Shiny App Demo

You can view a demo of the Shiny App on YouTube:

https://www.youtube.com/watch?v=tZbjV75L6F8

Or, you can check out the app online here:

https://stephanie-wuerth.shinyapps.io/MFA-wine/

References

Abdi, H., Williams, L. J., & Valentin, D. (2013). Multiple factor analysis: principal component analysis for multitable and multiblock data sets. Wiley Interdisciplinary reviews: computational statistics, 5(2), 149-179.

Pages, Jérôme. "Multiple factor analysis: Main features and application to sensory data." Revista Colombiana de Estadística 27.1 (2004): 1-26.

Abdi, Hervé. "Singular value decomposition (SVD) and generalized singular value decomposition." Encyclopedia of measurement and statistics (2007): 907-912.

============

This R package was created for a STAT243 Project. A description of the assignment can be found here. Package was written by Yulin Chen, Stephanie Wuerth, Eren Bilir, and Jim Oreluk.