MCA {FactoMineR} | R Documentation |
Performs Multiple Correspondence Analysis (MCA) with supplementary individuals, supplementary quantitative
variables and supplementary qualitative variables.
Missing values are treated as an additional level, categories which are rare can be ventilated
MCA(X, ncp = 5, ind.sup = NULL, quanti.sup = NULL, quali.sup = NULL, graph = TRUE, level.ventil = 0, axes = c(1,2), row.w = NULL)
X |
a data frame with n rows (individuals) and p columns (categorical variables) |
ncp |
number of dimensions kept in the results (by default 5) |
ind.sup |
a vector indicating the indexes of the supplementary individuals |
quanti.sup |
a vector indicating the indexes of the quantitative supplementary variables |
quali.sup |
a vector indicating the indexes of the qualitative supplementary variables |
graph |
boolean, if TRUE a graph is displayed |
level.ventil |
level under which the category is ventilated; by default, 0 and no nventilation is done |
axes |
a length 2 vector specifying the components to plot |
row.w |
an optional row weights (by default, uniform row weights) |
Returns a list including:
eig |
a matrix containing all the eigenvalues, the percentage of variance and the cumulative percentage of variance |
var |
a list of matrices containing all the results for the active variables (coordinates, square cosine, contributions, v.test) |
ind |
a list of matrices containing all the results for the active individuals (coordinates, square cosine, contributions) |
ind.sup |
a list of matrices containing all the results for the supplementary individuals (coordinates, square cosine) |
quanti.sup |
a matrix containing the coordinates of the supplementary quantitative variables (the correlation between a variable and an axis is equal to the variable coordinate on the axis) |
quali.sup |
a list of matrices with all the results for the supplementary qualitative variables (coordinates of each categories of each variables, square cosine and v.test which is a criterion with a Normal distribution) |
call |
a list with some statistics |
Returns the individuals factor map and the variables factor map.
Jeremy Mazet, Francois Husson Francois.Husson@agrocampus-ouest.fr
plotellipses
,print.MCA
, plot.MCA
, dimdesc
## Not run: data(poison) res.mca = MCA(poison, quali.sup = 3:4, quanti.sup = 1:2) plotellipses(res.mca) ## End(Not run)