View source: R/ggadd_ellipses.R

ggadd_ellipses | R Documentation |

Adds confidence ellipses for a categorical variable to a MCA cloud of individuals, using the ggplot2 framework.

ggadd_ellipses(p, resmca, var, sel=1:nlevels(var), axes=c(1,2), level=0.05, label=TRUE, label.size=3, col=NULL, size=0.5, points=TRUE, legend='right')

`p` |
ggplot object with the cloud of variables |

`resmca` |
object of class |

`var` |
Factor. The categorical variable used to plot ellipses. |

`sel` |
numeric vector of indexes of the categories to plot (by default, ellipses are plotted for every categories) |

`axes` |
numeric vector of length 2, specifying the components (axes) to plot. Default is c(1,2). |

`level` |
The level at which to draw an ellipse (see |

`label` |
Logical. Should the labels of the categories be plotted at the center of ellipses ? Default is TRUE. |

`label.size` |
Size of the labels of the categories at the center of ellipses. Default is 3. |

`col` |
Colors for the ellipses and labels of the categories. Can be the name of a palette from the RcolorBrewer package, 'bw' for a black and white palette (uses |

`size` |
Size of the lines of the ellipses. Default is 0.5. |

`points` |
If TRUE (default), the points are coloured according to their subcloud. |

`legend` |
the position of legends ("none", "left", "right", "bottom", "top", or two-element numeric vector). Default is right. |

A confidence ellipse aims at measuring how the "true" mean point of a category differs from its observed mean point. This is achieved by constructing a confidence zone around the observed mean point. If we choose a conventional level alpha (e.g. 0.05), a (1 - alpha) (e.g. 95 percents) confidence zone is defined as the set of possible mean points that are not significantly different from the observed mean point.

a ggplot object

Nicolas Robette

Le Roux B. and Rouanet H., *Multiple Correspondence Analysis*, SAGE, Series: Quantitative Applications in the Social Sciences, Volume 163, CA:Thousand Oaks (2010).

Le Roux B. and Rouanet H., *Geometric Data Analysis: From Correspondence Analysis to Stuctured Data Analysis*, Kluwer Academic Publishers, Dordrecht (June 2004).

`ggcloud_variables`

, `ggcloud_indiv`

, `ggadd_supvar`

, `ggadd_corr`

, `ggadd_interaction`

, `ggadd_density`

, `ggadd_kellipses`

## Performs a specific MCA on 'Music' example data set ## ignoring every 'NA' (i.e. 'not available') categories, ## draws the cloud of categories ## and adds confidence ellipses for Age. data(Music) getindexcat(Music[,1:5]) mca <- speMCA(Music[,1:5],excl=c(3,6,9,12,15)) p <- ggcloud_indiv(mca, col='lightgrey') ggadd_ellipses(p, mca, Music$Age)

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