Usage
randProj(data, seeds = 0, ...,
type = c("classification", "uncertainty", "errors"), ask = TRUE,
quantiles = c(0.75,0.95), symbols, scale = FALSE, identify = FALSE,
CEX = 1, PCH = ".", xlim, ylim)
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.
seeds
A vector of integers between 0 and 1000, specifying seeds for
the random projections. The default value is the single seed 0.
...
Any number of the following:
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
type
Any subset of c("classification","uncertainty","errors")
. The
function will produce the corresponding plot if it has been supplied
sufficient information to do so. If more than one plot is possible
then users will be asked to choo
ask
A logical variable indicating whether or not a menu should be produced
when more than one plot is possible.
The default is ask=TRUE
.
quantiles
A vector of length 2 giving quantiles used in plotting
uncertainty. The smallest symbols correspond to the smallest
quantile (lowest uncertainty), medium-sized (open) symbols to points
falling between the given quantiles, and large (filled) sy
symbols
Either an integer or character vector assigning a plotting symbol to
each unique class classification
. Elements in symbols
correspond to classes in classification
in order of
appearance in classific
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
identify
A logical variable indicating whether or not to add a title to the plot
identifying the dimensions used.
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 ".".
xlim, ylim
Arguments specifying bounds for the ordinate, abscissa of the plot.
This may be useful for when comparing plots.
References
C. Fraley and A. E. Raftery (2002a).
Model-based clustering, discriminant analysis, and density estimation.
Journal of the American Statistical Association 97:611-631.
See http://www.stat.washington.edu/mclust.
C. Fraley and A. E. Raftery (2002b).
MCLUST:Software for model-based clustering, density estimation and
discriminant analysis.
Technical Report, Department of Statistics, University of Washington.
See http://www.stat.washington.edu/mclust.