Plots a Multiple Correspondence Analysis cloud of individuals.
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")
object of class
If 'i', points are plotted. If 'inames', labels of individuals are plotted.
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.
numeric vector of length 2, specifying the components (axes) to plot. Default is c(1,2).
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".
Size of the points of individuals. Default is 0.5.
Transparency of the points or labels of individuals. Default is 0.6.
type="inames"", should labels of individuals be repeled ? Default is FALSE.
Size of the labels of individuals. Default is 2.
If NULL (default), no density layer is added. If "contour", density is plotted with contours. If "hex", density is plotted with hexagon bins.
character string. The color of the contours. Only used if density="contour".
integer. The number of bins in both vertical and horizontal directions. Only used if
character string. The name of a viridis palette for hexagon bins. Only used if
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.
col argument is a factor, points or labels are colored according to the categories of the factor, using the default
ggplot2 palette. The palette can be customized using any
scale_color_* function, such as
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).
# 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)