mvdalab (version 1.7)

ellipse.mvdalab: Ellipses, Data Ellipses, and Confidence Ellipses

Description

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

Usage

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, ...)

Value

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

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.

Author

Nelson Lee Afanador ()

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.

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

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