Ellipses of bootstrap validation (supplementary variables)

Ellipses for bootstrap validation of MCA, through the computation of the coordinates of supplementary variables for bootstrap replications of the data.

ggbootvalid_supvars(resmca, vars = NULL, axes = c(1,2), K = 30,
                    ellipse = "norm", level = 0.95,
                    col = NULL, active = FALSE, legend = "right")

Arguments

resmca: object of class speMCA.
vars: A data frame of categorical supplementary variables. All these variables should be factors.
axes: numeric vector of length 2, specifying the components (axes) to plot. Default is c(1,2).
K: integer. Number of bootstrap replications (default is 30).
ellipse: character string. The type of ellipse. The default "norm" assumes a multivariate normal distribution, "t" assumes a multivariate t-distribution, and "euclid" draws a circle with the radius equal to level, representing the euclidean distance from the center.
level: numerical value. The level at which to draw an ellipse, or, if ellipse="euclid", the radius of the circle to be drawn.
col: Character string. Color name for the ellipses and labels of the categories. If NULL (default), the default ggplot2 palette is used, with one color per variable.
active: logical. If TRUE, the labels of active variables are added to the plot in lightgray. Default is FALSE.
legend: the position of legends ("none", "left", "right", "bottom", "top", or two-element numeric vector). Default is right.

Details

The bootstrap technique is used here as an internal (and non-parametric) validation procedure of the results of a multiple correspondence analysis. For supplementary variables, only partial bootstrap is possible. The partial bootstrap does not compute new MCAs: it projects bootstrap replications of the initial data as supplementary elements of the MCA. See references for more details.

The default parameters for ellipses assume a multivariate normal distribution drawn at level 0.95.

Value

a ggplot2 object

Note

If col argument is NULL, ellipses and labels are colored according to the variables, using the default ggplot2 palette. The palette can be customized using any scale_color_* function, such as scale_color_brewer(), scale_color_grey() or scale_color_manual().

References

Lebart L. (2006). "Validation Techniques in Multiple Correspondence Analysis". In M. Greenacre et J. Blasius (eds), Multiple Correspondence Analysis and related techniques, Chapman and Hall/CRC, p.179-196.

Lebart L. (2007). "Which bootstrap for principal axes methods?". In P. Brito et al. (eds), Selected Contributions in Data Analysis and Classification, Springer, p.581-588.

Author

Nicolas Robette

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)
# bootstrap validation ellipses
# for three supplementary variables
sup <- Taste[,c("Gender", "Age", "Educ")]
ggbootvalid_supvars(mca, sup)