tab.disjonctif

algebra

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).

Francois Husson

FactoMineR

Multivariate Exploratory Data Analysis and Data Mining

tab.disjonctif function

<dl> <dt>tab</dt>
<dd>a data frame with factors</dd></dl>

Arguments

Make a disjonctif table — tab.disjonctif

<dl>

 <dt>tab</dt>
<dd>a data frame with factors</dd>

</dl>

tab.disjonctif: Make a disjonctif table

Description

Usage

Value

Arguments