GDAtools (version 2.1)

ggcloud_indiv: Plot of the cloud of individuals

Description

Plots a Multiple Correspondence Analysis cloud of individuals.

Usage

ggcloud_indiv(resmca, type = "i", points = "all", axes = c(1,2), 
col = "dodgerblue4", point.size = 0.5, alpha = 0.6,
repel = FALSE, text.size = 2,
density = NULL, col.contour = "darkred", hex.bins = 50, hex.pal = "viridis")

Value

a ggplot2 object

Arguments

resmca

object of class MCA, speMCA, csMCA, stMCA or multiMCA

type

If 'i', points are plotted. If 'inames', labels of individuals are plotted.

points

character string. If 'all' all points are plotted (default). If 'besth' only those who contribute most to horizontal axis are plotted. If 'bestv' only those who contribute most to vertical axis are plotted. If 'besthv' only those who contribute most to horizontal or vertical axis are plotted. If 'best' only those who contribute most to the plane are plotted.

axes

numeric vector of length 2, specifying the components (axes) to plot. Default is c(1,2).

col

If a factor, points or labels are colored according to their category regarding this factor. If a string with color name, every points or labels have the same color. Default is "dodgerblue4".

point.size

Size of the points of individuals. Default is 0.5.

alpha

Transparency of the points or labels of individuals. Default is 0.6.

repel

Logical. When type="inames"", should labels of individuals be repeled ? Default is FALSE.

text.size

Size of the labels of individuals. Default is 2.

density

If NULL (default), no density layer is added. If "contour", density is plotted with contours. If "hex", density is plotted with hexagon bins.

col.contour

character string. The color of the contours. Only used if density="contour".

hex.bins

integer. The number of bins in both vertical and horizontal directions. Only used if density="hex".

hex.pal

character string. The name of a viridis palette for hexagon bins. Only used if density="hex".

Author

Anton Perdoncin, Nicolas Robette

Details

Sometimes the dots are too many and overlap. It is then difficult to get an accurate idea of the distribution of the cloud of individuals. The density argument allows you to add an additional layer to represent the density of points in the plane, in the form of contours or hexagonal areas.

References

Le Roux B. and Rouanet H., Multiple Correspondence Analysis, SAGE, Series: Quantitative Applications in the Social Sciences, Volume 163, CA:Thousand Oaks (2010).

Le Roux B. and Rouanet H., Geometric Data Analysis: From Correspondence Analysis to Stuctured Data Analysis, Kluwer Academic Publishers, Dordrecht (June 2004).

See Also

ggcloud_variables

Examples

# specific MCA of Taste example data set
data(Taste)
junk <- c("FrenchPop.NA", "Rap.NA", "Rock.NA", "Jazz.NA", "Classical.NA",
          "Comedy.NA", "Crime.NA", "Animation.NA", "SciFi.NA", "Love.NA", 
          "Musical.NA")
mca <- speMCA(Taste[,1:11], excl = junk)
# cloud of individuals
ggcloud_indiv(mca)
# points are colored according to gender
ggcloud_indiv(mca, col=Taste$Gender)
# a density layer of contours is added
ggcloud_indiv(mca, density = "contour")
# a density layer of hexagon bins is added
ggcloud_indiv(mca, density = "hex", hex.bin = 10)