ellipse.default {ellipse} | R Documentation |
This function produces an ellipse representing a pairwise confidence region for two parameters, given a covariance or correlation matrix or just a correlation, and a position.
ellipse.default(x, scale=c(1, 1), centre=c(0, 0), level=0.95, t=sqrt(qchisq(level,2)), which=c(1, 2), npoints=100)
x |
The parameter x should be a correlation between -1 and 1 or a square positive definite matrix at least 2x2 in size. It will be treated as the correlation or covariance of a multivariate normal distribution. |
scale |
If x is a correlation matrix, then the standard deviations of each parameter can be given in the scale parameter. This defaults to c(1,1), so no rescaling will be done. |
centre |
The centre of the ellipse will be at this position. Default c(0,0). |
level |
The confidence level of a pairwise confidence region. The default is 0.95, for a 95% region. This is used to control the size of the ellipse being plotted. A vector of levels may be used. |
t |
The size of the ellipse may also be controlled by specifying the value of a t-statistic on its boundary. This defaults to the appropriate value for the confidence region. |
which |
This parameter selects which pair of variables from the matrix will be plotted. The default is the first 2. |
npoints |
The number of points used in the ellipse. Default is 100. |
The (cos(theta+d/2), cos(theta-d/2)) parametrization of an ellipse is used, where cos(d) is the correlation of the parameters.
An npoints x 2 matrix is returned with columns named according to the row names of the matrix x (default 'x' and 'y'), suitable for plotting.
Murdoch, D.J. and Chow, E.D. (1994). A graphical display of large correlation matrices. Mathematical preprint #1994-09, Department of Mathematics and Statistics, Queen's University, Kingston, Canada.
ellipse
# Make a 2 x 2 covariance matrix, and plot the corresponding 95% # confidence region cov <- matrix(c(1,0.5,0.5,1), 2,2) plot(ellipse(cov))