| ellipse3d {rgl} | R Documentation |
A generic function and several methods returning an ellipsoid or other outline of a confidence region for three parameters.
ellipse3d(x, ...)
## Default S3 method:
ellipse3d(x, scale = c(1, 1, 1), centre = c(0, 0, 0), level = 0.95,
t = sqrt(qchisq(level, 3)), which = 1:3, subdivide = 4, ...)
## S3 method for class 'lm':
ellipse3d(x, which = 1:3, level = 0.95, t = sqrt(3 * qf(level,
3, x$df.residual)), ...)
## S3 method for class 'glm':
ellipse3d(x, which = 1:3, level = 0.95, t, dispersion, ...)
## S3 method for class 'nls':
ellipse3d(x, which = 1:3, level = 0.95, t = sqrt(3 * qf(level,
3, s$df[2])), ...)
x |
An object. In the default method the parameter x should be a
square positive definite matrix at least 3x3
in size. It will be treated as the correlation or covariance
of a multivariate normal distribution.
|
... |
Additional parameters to pass to the default method or to qmesh3d.
|
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, 1),
so no rescaling will be done.
|
centre |
The centre of the ellipse will be at this position. |
level |
The confidence level of a simulataneous confidence region. The default is 0.95, for a 95% region. This is used to control the size of the ellipsoid. |
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 variables from the object will be plotted. The default is the first 3. |
subdivide |
This controls the number of subdivisions (see subdivision3d)
used in constructing the ellipsoid. Higher numbers give a smoother shape.
|
dispersion |
The value of dispersion to use. If specified, it is treated as fixed,
and chi-square limits for t are used. If missing, it is
taken from summary(x).
|
A qmesh3d object representing the ellipsoid.
# Plot a random sample and an ellipsoid of concentration corresponding to a 95%
# probability region for a
# trivariate normal distribution with mean 0, unit variances and
# correlation 0.8.
if (require(MASS)) {
Sigma <- matrix(c(10,3,0,3,2,0,0,0,1), 3,3)
Mean <- 1:3
x <- mvrnorm(1000, Mean, Sigma)
open3d()
plot3d(x, size=3, box=FALSE)
plot3d( ellipse3d(Sigma, centre=Mean), col="green", alpha=0.5, add = TRUE)
}
# Plot the estimate and joint 90% confidence region for the displacement and cylinder
# count linear coefficients in the mtcars dataset
data(mtcars)
fit <- lm(mpg ~ disp + cyl , mtcars)
open3d()
plot3d(ellipse3d(fit, level = 0.90), col="blue", alpha=0.5, aspect=TRUE)