FactoMineR - Multivariate Exploratory Data Analysis and Data Mining

Exploratory data analysis methods to summarize, visualize and describe datasets. The main principal component methods are available, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, Multiple Factor Analysis when variables are structured in groups, etc. and hierarchical cluster analysis. F. Husson, S. Le and J. Pages (2017).

Last updated 4 months ago

14.76 score 42 stars 107 packages 5.0k scripts 107k downloads

Factoshiny - Perform Factorial Analysis from 'FactoMineR' with a Shiny Application

Perform factorial analysis with a menu and draw graphs interactively thanks to 'FactoMineR' and a Shiny application.

Last updated 1 years ago

7.36 score 9 stars 132 scripts 4.8k downloads

SensoMineR - Sensory Data Analysis

Statistical Methods to Analyse Sensory Data. SensoMineR: A package for sensory data analysis. S. Le and F. Husson (2008).

Last updated 10 months ago

5.19 score 1 packages 104 scripts 770 downloads

FactoInvestigate - Automatic Description of Factorial Analysis

Brings a set of tools to help and automatically realise the description of principal component analyses (from 'FactoMineR' functions). Detection of existing outliers, identification of the informative components, graphical views and dimensions description are performed threw dedicated functions. The Investigate() function performs all these functions in one, and returns the result as a report document (Word, PDF or HTML).

Last updated 1 years ago

4.91 score 1 stars 1 packages 66 scripts 4.1k downloads