crimcoords  R Documentation 
Compute the discriminant coordinates or crimcoords obtained by projecting the observed data from multiple groups onto the discriminant subspace. The optimal projection subspace is given by the linear transformation of the original variables that maximizes the ratio of the betweengroups covariance (which represents groups separation) to the pooled withingroup covariance (which represents withingroup dispersion).
crimcoords(data, classification, numdir = NULL, unbiased = FALSE, plot = TRUE, ...) ## S3 method for class 'crimcoords' plot(x, ...)
data 
A numeric vector, matrix, or data frame of observations. Categorical variables are not allowed. If a matrix or data frame, rows correspond to observations and columns correspond to variables. 
classification 
A vector (numerical, character string, or factor) giving the groups classification (either the known class labels or the estimated clusters) for the observed data. 
numdir 
An integer value specifying the number of directions of the discriminant subspace to return. If not provided, the maximal number of directions are returned (which is given by the number of nonnull eigenvalues, the minimum among the number of variables and the number of groups minus one). However, since the effectiveness of the discriminant coordinates in highlighting the separation of groups is decreasing, it might be useful to provide a smaller value, say 2 or 3. 
unbiased 
A logical specifying if unbiased estimates should be used for the
betweengroups and withingroups covariances. By default

plot 
A logical specifying if a graph of discriminant coordinates should be produced (default) or not. 
x 
An object of class 
... 
further arguments passed to or from other methods. 
A list of class crimcoords
with the following components:
means 
A matrix of withingroups means. 
B 
The betweengroups covariance matrix. 
W 
The pooled withingroups covariance matrix. 
evalues 
A vector of eigenvalues. 
basis 
A matrix of eigenvectors specifying the basis of the discriminant subspace. 
projection 
A matrix of projected data points onto the discriminant subspace. 
classification 
A vector giving the groups classification. 
If plot = TRUE
(default) a graph of data points projected onto
the discriminant coordinate or crimcoords subspace is also produced.
Luca Scrucca luca.scrucca@unipg.it
Gnanadesikan, R. (1977) Methods for Statistical Data Analysis of Multivariate Observations. John Wiley 1& Sons, Sec. 4.2.
Flury, B. (1997) A First Course in Multivariate Statistics. Springer, Sec. 7.3.
MclustDR
, clPairs
.
# discriminant coordinates for the iris data using known classes data("iris") CRIMCOORDS = crimcoords(iris[,5], iris$Species) CRIMCOORDS # banknote data data("banknote") # discriminant coordinate on known classes CRIMCOORDS = crimcoords(banknote[,1], banknote$Status) CRIMCOORDS # discriminant coordinates on estimated clusters mod = Mclust(banknote[,1]) CRIMCOORDS = crimcoords(banknote[,1], mod$classification, plot = FALSE) plot(CRIMCOORDS$projection, type = "n") text(CRIMCOORDS$projection, cex = 0.8, labels = strtrim(banknote$Status, 2), col = mclust.options("classPlotColors")[1:mod$G][mod$classification])
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