desDA
From DiscriMiner v0.129
by Gaston Sanchez
Descriptive Discriminant Analysis
Performs a Descriptive Discriminant Analysis (a.k.a. Factorial Discriminant Analysis from the french Analyse Factorielle Discriminante)
Usage
desDA(variables, group, covar = "within")
Arguments
 variables
 matrix or data frame with explanatory variables
 group
 vector or factor with group memberships
 covar
 character string indicating the covariance
matrix to be used. Options are
"within"
and"total"
Details
When covar="within"
the estimated pooled
withinclass covariance matrix is used in the
calculations. When covar="total"
the total
covariance matrix is used in the calculations. The
difference between covar="within"
and
covar="total"
is in the obtained eigenvalues.
The estiamted pooled withinclass covariance matrix is
actually the withinclass covariance matrix divided by
the number of observations minus the number of classes
(see getWithin
)
Value

An object of class
 power
 table with discriminant power of the explanatory variables
 values
 table of eigenvalues
 discrivar
 table of discriminant variables, i.e. the coefficients of the linear discriminant functions
 discor
 table of correlations between the variables and the discriminant axes
 scores
 table of discriminant scores for each observation
"desda"
, basically a list with
the following elementsReferences
Lebart L., Piron M., Morineau A. (2006) Statistique Exploratoire Multidimensionnelle. Dunod, Paris.
See Also
Examples
## Not run:
# # load bordeaux wines dataset
# data(bordeaux)
#
# # descriptive discriminant analysis with within covariance matrix
# my_dda1 = desDA(bordeaux[,2:5], bordeaux$quality)
# my_dda1
#
# # descriptive discriminant analysis with total covariance matrix
# my_dda2 = desDA(bordeaux[,2:5], bordeaux$quality, covar="total")
# my_dda2
#
# # plot factor coordinates with ggplot
# library(ggplot2)
# bordeaux$f1 = my_dda1$scores[,1]
# bordeaux$f2 = my_dda1$scores[,2]
# ggplot(data=bordeaux, aes(x=f1, y=f2, colour=quality)) +
# geom_hline(yintercept=0, colour="gray70") +
# geom_vline(xintercept=0, colour="gray70") +
# geom_text(aes(label=year), size=4) +
# opts(title="Discriminant Map  Bordeaux Wines (years)")
# ## End(Not run)
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