plot-methods: Plotting of a class ['Mixmod'] In Rmixmod: Classification with Mixture Modelling

Description

Plotting data from a [`Mixmod`] object using parameters and partition to distinguish the different clusters.

Usage

 ```1 2 3``` ```## S4 method for signature 'Mixmod' plot(x, y, showOnly = NULL, withResult = NULL, hist_x_dim = 10000, ...) ```

Arguments

 `x` an object of class [`Mixmod`] `y` a list of variables to plot (subset). Variables names or indices. Only in a quantitative case. `showOnly` show only (...) `withResult` with result (...) `hist_x_dim` Histogram dimension (???) `...` further arguments passed to or from other methods

Details

For quantitative case, ellipsoids (i.e. linear transformations of hyperspheres) centered at the mean are drawn using the parameters computed by MIXMOD. The directions of the principal axes of the ellipsoids are given by the eigenvectors of the covariance matrix Σ. The squared relative lengths of the principal axes are given by the corresponding eigenvalues. A 1-dimensional representation of variables with the densities is drawn on the diagonal.

For qualitative case, a Multiple Correspondance Analysis is performed to get a 2-dimensional representation of the data set. Bigger symbol means that observations are similar.

`plot`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12``` ``` ## for quantitative case data(iris) xem <- mixmodCluster(iris[1:4],3) plot(xem) plot(xem,c(1,3)) plot(xem,c("Sepal.Length","Sepal.Width")) ## for qualitative case data(birds) xem2 <- mixmodCluster(birds,2) plot(xem2) legend("bottomleft",c("Cluster1","Cluster2"),col=c(2,3),pch=c(1,2)) ```