Description Usage Arguments Value Examples
A generic function and several methods returning an ellipsoid or other outline of a confidence region for three parameters.
| 1 2 3 4 5 6 7 8 9 10 11 12 | 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 = 3, smooth = TRUE, ...)
## 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  | 
| ... | Additional parameters to pass to the default method or to  | 
| scale | If  | 
| 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  | 
| smooth | If  | 
| dispersion | The value of dispersion to use.  If specified, it is treated as fixed,
and chi-square limits for  | 
A mesh3d object representing the ellipsoid.
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | # 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")) {
  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)
 | 
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