View source: R/bootvalid_supvars.R
bootvalid_supvars | R Documentation |
Bootstrap validation of MCA, through the computation of the coordinates of supplementary variables for bootstrap replications of the data.
bootvalid_supvars(resmca, vars = NULL, axes = c(1,2), K = 30)
resmca |
object of class |
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). |
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).
A data frame with the following elements :
varcat |
Names of the active categories |
K |
Indexes of the bootstrap replications |
dim.x |
Bootstrap coordinates on the first selected axis |
dim.y |
Bootstrap coordinates on the second selected axis |
Nicolas Robette
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.
ggbootvalid_supvars
, bootvalid_variables
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")
resmca <- speMCA(Taste[,1:11], excl = junk)
supvars <- Taste[,c("Gender", "Age", "Educ")]
bv <- bootvalid_supvars(resmca, supvars, K = 5)
str(bv)
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