`ellipse3d.Rd`

A generic function and several methods returning an ellipsoid or other outline of a confidence region for three parameters.

```
ellipse3d(x, ...)
# S3 method for default
ellipse3d(x, scale = c(1, 1, 1), centre = c(0, 0, 0), level = 0.95,
t = sqrt(qchisq(level, 3)), which = 1:3, subdivide = 3, smooth = TRUE, ...)
# S3 method for lm
ellipse3d(x, which = 1:3, level = 0.95, t = sqrt(3 * qf(level,
3, x$df.residual)), ...)
# S3 method for glm
ellipse3d(x, which = 1:3, level = 0.95, t, dispersion, ...)
# S3 method for nls
ellipse3d(x, which = 1:3, level = 0.95, t = sqrt(3 * qf(level,
3, s$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 simultaneous 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.- smooth
If

`TRUE`

, smooth interpolation of normals is used; if`FALSE`

, a faceted ellipsoid will be displayed.- 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 `mesh3d`

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 (requireNamespace("MASS", quietly = TRUE)) {
Sigma <- matrix(c(10, 3, 0, 3, 2, 0, 0, 0, 1), 3, 3)
Mean <- 1:3
x <- MASS::mvrnorm(1000, Mean, Sigma)
open3d()
plot3d(x, 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)
```