R: Plot two-dimensional data modelled by an MVN mixture

mclust2Dplot {mclust} | R Documentation

## Plot two-dimensional data modelled by an MVN mixture

### Description

Plot two-dimensional data given parameters of an MVN mixture model for the data.

### Usage

    mclust2Dplot(data, parameters = NULL, z = NULL,
                 classification = NULL, truth = NULL, uncertainty = NULL,
                 what = c("classification", "uncertainty", "error"),
                 addEllipses = TRUE, fillEllipses = mclust.options("fillEllipses"),
                 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: `pro` Mixing proportions for the components of the mixture. There should one more mixing proportion than the number of Gaussian components if the mixture model includes a Poisson noise term. `mean` The mean for each component. If there is more than one component, this is a matrix whose kth column is the mean of the kth component of the mixture model. `variance` A list of variance parameters for the model. The components of this list depend on the model specification. See the help file for `mclustVariance` for details.
`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), `"error"`, `"uncertainty"`.
`addEllipses` | A logical indicating whether or not to add ellipses with axes corresponding to the within-cluster covariances.
`fillEllipses` | A logical specifying whether or not to fill ellipses with transparent colors when `addEllipses = TRUE`.
`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.

### Value

A plot showing the data, together with the location of the mixture components, classification, uncertainty, and/or classification errors.

### See Also

`surfacePlot`, `clPairs`, `coordProj`, `mclust.options`

### Examples

    ## Not run:
    faithfulModel <- Mclust(faithful)

    mclust2Dplot(faithful, parameters=faithfulModel$parameters,
                 z=faithfulModel$z, what = "classification", main = TRUE)

    mclust2Dplot(faithful, parameters=faithfulModel$parameters,
                 z=faithfulModel$z, what = "uncertainty", main = TRUE)

    ## End(Not run)

[Package mclust version 5.4.5 Index]