```
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

`c(1,2)`

, in which the first
dimension is plotted against the second.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:
[object Object],[object Object]

z

A matrix in which the *i* belonging to the *k*th class.
Used to compute

`[i,k]`

th entry gives the
probability of observation `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"`

.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 in

`classification`

. Elements in `colors`

correspond to classes in order of appearance in the sequence of
observations (the order usedcolors

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 fuscale

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`

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.

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]))
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)
```

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