Usage
mclust2Dplot(data, parameters = NULL, z = NULL, classification = NULL, truth = NULL, uncertainty = NULL, what = c("classification","uncertainty","errors"), addEllipses = TRUE, symbols = NULL, colors = NULL, xlim = NULL, ylim = NULL, xlab = NULL, ylab = NULL, scale = FALSE, CEX = 1, PCH = ".", main = FALSE, swapAxes = FALSE, ...)
Arguments
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.
In this case the data are two dimensional, so there are two columns.
parameters
A named list giving the parameters of an MCLUST model,
used to produce superimposing ellipses on the plot.
The relevant components are as follows:
z
A matrix in which the [i,k]th entry gives the
probability of observation i belonging to the kth class.
Used to compute classification and
uncertainty if those arguments aren't available.
classification
A numeric or character vector representing a classification of
observations (rows) of data. If present argument z
will be ignored.
truth
A numeric or character vector giving a known
classification of each data point.
If classification
or z is also present,
this is used for displaying classification errors.
uncertainty
A numeric vector of values in (0,1) giving the
uncertainty of each data point. If present argument z
will be ignored.
what
Choose from one of the following three options: "classification"
(default), "errors", "uncertainty".
addEllipses
A logical indicating whether or not to add ellipses with axes corresponding
to the within-cluster covariances.
symbols
Either an integer or character vector assigning a plotting symbol to each
unique class in classification. Elements in colors
correspond to classes in order of appearance in the sequence of
observations (the order used by the function unique).
The default is given by mclust.options("classPlotSymbols").
colors
Either an integer or character vector assigning a color to each
unique class in classification. Elements in colors
correspond to classes in order of appearance in the sequence of
observations (the order used by the function unique).
The default is given is mclust.options("classPlotColors").
xlim, ylim
Optional argument specifying bounds for the ordinate, abscissa of the plot.
This may be useful for when comparing plots.
xlab, ylab
Optional argument specifying labels for the x-axis and y-axis.
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: scale=FALSE
CEX
An argument specifying the size of the plotting symbols.
The default value is 1.
PCH
An argument specifying the symbol to be used when a classificatiion
has not been specified for the data. The default value is a small dot ".".
main
A logical variable or NULL indicating whether or not to add a title
to the plot identifying the dimensions used.
swapAxes
A logical variable indicating whether or not the axes should be swapped
for the plot.
...
Other graphics parameters.
Side Effects
A plot showing the data, together with the location of the mixture
components, classification, uncertainty, and/or classification errors.References
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, A. E. Raftery, T. B. Murphy and L. Scrucca (2012).
mclust Version 4 for R: Normal Mixture Modeling for Model-Based
Clustering, Classification, and Density Estimation.
Technical Report No. 597, Department of Statistics, University of Washington.