This function draws econfidence ellipses for covariance and correlation matrices derived from from either a matrix or dataframe.

1 2 3 |

`data` |
A dataframe |

`center` |
2-element vector with coordinates of center of ellipse. |

`radius` |
Use of the Chi or F Distributions for setting the radius of the confidence ellipse |

`scale` |
use correlation or covariance matrix |

`segments` |
number of line-segments used to draw ellipse. |

`level` |
draw elliptical contours at these (normal) probability or confidence levels. |

`pch` |
symbols to use for scores |

`size` |
size to use for scores |

`alpha` |
transparency of scores |

`plot.points` |
Should the points be added to the graph. |

`verbose` |
output results as a data frame |

`...` |
additional arguments. Currently ignored. |

`ellipse`

uses the singular value decomposition in order to generate the desired confidence regions. The default confidence ellipse is based on the chisquare statistic.

Returns a graph with the ellipses at the stated as levels, as well as the ellipse coordinates.

Nelson Lee Afanador (nelson.afanador@mvdalab.com)

Fox, J. (2008) Applied Regression Analysis and Generalized Linear Models, Second Edition. Sage.

Fox, J. and Weisberg, S. (2011) An R Companion to Applied Regression, Second Edition, Sage.

1 2 3 | ```
data(iris)
ellipse.mvdalab(iris[, 1:2], plot.points = FALSE)
ellipse.mvdalab(iris[, 1:2], center = colMeans(iris[, 1:2]), plot.points = TRUE)
``` |

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