| ellipse.mvdalab {mvdalab} | R Documentation |
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, ...)
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.
Author(s)
Nelson Lee Afanador (nelson.afanador@mvdalab.com)
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)