Description Usage Arguments Value See Also Examples
Plots random projections given multidimensional data and parameters of an MVN mixture model for the data.
1 2 3 4 5 6 7 8  randProj(data, seeds = NULL, parameters = NULL, z = NULL,
classification = NULL, truth = NULL, uncertainty = NULL,
what = c("classification", "error", "uncertainty"),
quantiles = c(0.75, 0.95),
addEllipses = TRUE, fillEllipses = mclust.options("fillEllipses"),
symbols = NULL, colors = NULL, scale = FALSE,
xlim = NULL, ylim = NULL, xlab = NULL, ylab = NULL,
cex = 1, PCH = ".", main = FALSE, ...)

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. 
seeds 
An integer value or a vector of integer values to be used as seed for
random number generation. If multiple values are provided, then each seed
should produce a different projection.
By default, a single seed is drawn randomnly, so each call of

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 
classification 
A numeric or character vector representing a classification of
observations (rows) of 
truth 
A numeric or character vector giving a known
classification of each data point.
If 
uncertainty 
A numeric vector of values in (0,1) giving the
uncertainty of each data point. If present argument 
what 
Choose from one of the following three options: 
quantiles 
A vector of length 2 giving quantiles used in plotting uncertainty. The smallest symbols correspond to the smallest quantile (lowest uncertainty), mediumsized (open) symbols to points falling between the given quantiles, and large (filled) symbols to those in the largest quantile (highest uncertainty). The default is (0.75,0.95). 
addEllipses 
A logical indicating whether or not to add ellipses with axes
corresponding to the withincluster covariances in case of

fillEllipses 
A logical specifying whether or not to fill ellipses with transparent
colors when 
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 
Optional arguments specifying bounds for the ordinate, abscissa of the plot. This may be useful for when comparing plots. 
xlab, ylab 
Optional arguments specifying the labels for, respectively, the horizontal and vertical axis. 
cex 
A numerical value 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 
... 
Other graphics parameters. 
A plot showing a random twodimensional projection of the data, together with the location of the mixture components, classification, uncertainty, and/or classification errors.
The function also returns an invisible list with components basis
, the randomnly generated basis of the projection subspace, data
, a matrix of projected data, and mu
and sigma
the component parameters transformed to the projection subspace.
clPairs
,
coordProj
,
mclust2Dplot
,
mclust.options
1 2 3 4 5 6 7 8  est < meVVV(iris[,5], unmap(iris[,5]))
par(pty = "s", mfrow = c(1,1))
randProj(iris[,5], seeds=1:3, parameters = est$parameters, z = est$z,
what = "classification", main = TRUE)
randProj(iris[,5], seeds=1:3, parameters = est$parameters, z = est$z,
truth = iris[,5], what = "error", main = TRUE)
randProj(iris[,5], seeds=1:3, parameters = est$parameters, z = est$z,
what = "uncertainty", main = TRUE)

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