coordProj {mclust} | R Documentation |
Plots coordinate projections given multidimensional data and parameters of an MVN mixture model for the data.
coordProj(data, dimens=c(1,2), parameters=NULL, z=NULL, classification=NULL, truth=NULL, uncertainty=NULL, what = c("classification", "errors", "uncertainty"), quantiles = c(0.75, 0.95), symbols=NULL, colors=NULL, scale = FALSE, xlim=NULL, ylim=NULL, CEX = 1, PCH = ".", identify = 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. |
dimens |
A vector of length 2 giving the integer dimensions of the
desired coordinate projections. The default is
|
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), medium-sized (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). |
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. |
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 ".". |
identify |
A logical variable indicating whether or not to add a title to the plot identifying the dimensions used. |
... |
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, revised 2010). MCLUST Version 3 for R: Normal Mixture Modeling and Model-Based Clustering, Technical Report no. 504, Department of Statistics, University of Washington.
clPairs
,
randProj
,
mclust2Dplot
,
mclustOptions
est <- meVVV(iris[,-5], unmap(iris[,5])) ## Not run: par(pty = "s", mfrow = c(1,1)) coordProj(iris[,-5], dimens=c(2,3), parameters = msEst$parameters, z = est$z, what = "classification", identify = TRUE) coordProj(iris[,-5], dimens=c(2,3), parameters = msEst$parameters, z = est$z, truth = iris[,5], what = "errors", identify = TRUE) coordProj(iris[,-5], dimens=c(2,3), parameters = msEst$parameters, z = est$z, what = "uncertainty", identify = TRUE) ## End(Not run)