plot.mclustDAtrain {mclust} | R Documentation |
Plots representation of the models produced by
mclustDAtrain
. For multidimensional data,
the plot is a coordinate projection and the ellipses shown correspond to
the covariance matrices.
## S3 method for class 'mclustDAtrain' plot(x, data, dimens=c(1,2), symbols=NULL, colors=NULL, scale = FALSE, xlim=NULL, ylim=NULL, CEX = 1, ...)
x |
An object produced by a call to |
data |
A numeric 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. |
dimens |
A vector of length 2 giving the integer dimensions of the
desired coordinate projections. The default is
|
symbols |
Either an integer or character vector assigning a plotting symbol to each
unique class in |
colors |
Either an integer or character vector assigning a color to each
unique class in |
scale |
A logical variable indicating whether or not the two chosen
dimensions should be plotted on the same scale, and
thus preserve the shape of the distribution.
Default: |
xlim, ylim |
Arguments specifying bounds for the ordinate, abscissa of the plot. This may be useful for when comparing plots. |
CEX |
An argument specifying the size of the plotting symbols. The default value is 1. |
... |
Other graphics parameters. |
A plot showing a two-dimensional coordinate projection of the data, together with the location of the mixture components, classification, uncertainty, and/or classification errors.
C. Fraley and A. E. Raftery (2002). Model-based clustering, discriminant analysis, and density estimation. Journal of the American Statistical Association 97:611-631.
C. Fraley and A. E. Raftery (2006). MCLUST Version 3 for R: Normal Mixture Modeling and Model-Based Clustering, Technical Report no. 504, Department of Statistics, University of Washington.
coordProj
,
mclust1Dplot
,
mclust2Dplot
,
mclustOptions
odd <- seq(from = 1, to = nrow(iris), by = 2) irisTrain <- mclustDAtrain(data = iris[odd,-5], labels = iris[odd,5]) ## Not run: plot(irisTrain, iris[odd,-5]) ## End(Not run)