Graphs for Correspondence Analysis

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Documentation for package ‘ggfacto’ version 0.4.0

Help Pages

axis_coord Coordinates of the Individuals on the Axes of an Analysis
benzecri_mrv Benzecri's modified rate of variance
clust_tab Describe Clusters with One Table
correspondence_analysis Correspondence Analysis of a Crosstab
eigenvalues The Eigenvalues of an Analysis
ggca Readable and Interactive Graph for Simple Correspondence Analysis
ggfacto The Graph of an Analysis
ggfacto_plot Graphs knitted at their own aspect ratio
ggfacto_summary The interpretation tables, and how they print
ggfacto_widget Widgets written to their own file
ggi Make a graph interactive
ggmca Readable and Interactive graph for multiple correspondence analysis
ggmca_3d Interactive 3D Plot for Multiple Correspondence Analyses (plotly::)
ggmca_data Readable and Interactive graph for multiple correspondence analysis
ggmca_initial_dims Plot Initial Dimensions (Active Variables) of Multiple Correspondence Analysis
ggmca_plot Readable and Interactive graph for multiple correspondence analysis
ggmca_with_base_ref Plot Initial Dimensions (Active Variables) on a Multiple Correspondence Analyses
ggpca Readable and Interactive Graph of the Individuals of a Principal Component Analysis
ggpca_3d Interactive 3D Plot for Principal Component Analyses (plotly::)
ggpca_cor_circle Correlation Circle Plot for Principal Component Analysis
ggsave2 Save a plot as image
hierarchical_clust Hierarchical Clustering on the Axes of an Analysis
interpret Interpret the Axes of an Analysis
is_in_analysis Which Rows an Analysis Was Made On
material_colors_dark Dark Material palette for MCA level names
material_colors_light Light Material palette for MCA points
MCA2 Multiple Correspondence Analysis
mca_interpret Interpret the Axes of an Analysis
mean_sd_tab Simple Mean and SD Summary (deprecated)
multiple_correspondence_analysis Multiple Correspondence Analysis
name_axes Name the Axes of an Analysis
PCA2 Principal Component Analysis
pca_interpret Interpret the Axes of an Analysis
principal_component_analysis Principal Component Analysis
print.ggfacto_summary The interpretation tables, and how they print
theme_facto A ggplot2 Theme for Geometrical Data Analysis