# ellipse.mvdalab: Ellipses, Data Ellipses, and Confidence Ellipses In mvdalab: Multivariate Data Analysis Laboratory

## Description

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

## Usage

 ```1 2 3``` ```ellipse.mvdalab(data, center = c(0, 0), radius = "chi", scale = TRUE, segments = 51, level = c(0.95, 0.99), plot.points = FALSE, pch = 1, size = 1, alpha = 0.5, verbose = FALSE, ...) ```

## Arguments

 `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.

## Details

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

## Value

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

## References

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.

## Examples

 ```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) ```

mvdalab documentation built on Nov. 17, 2017, 6 a.m.