Predict Method for Ellipsoid Objects
Compute points on the ellipsoid boundary, mostly for drawing.
predict.ellipsoid(object, n.out=201, ...) ## S3 method for class 'ellipsoid' predict(object, n.out=201, ...) ellipsoidPoints(A, d2, loc, n.half = 201)
object |
an object of class |
n.out, n.half |
half the number of points to create. |
A, d2, loc |
arguments of the auxilary |
... |
passed to and from methods. |
Note ellipsoidPoints
is the workhorse function of
predict.ellipsoid
a standalone function and method for
ellipsoid
objects, see ellipsoidhull
.
The class of object
is not checked; it must solely have valid
components loc
(length p), the p x p
matrix cov
(corresponding to A
) and d2
for the
center, the shape (“covariance”) matrix and the squared average
radius (or distance) or qchisq(*, p)
quantile.
Unfortunately, this is only implemented for p = 2, currently; contributions for p >= 3 are very welcome.
a numeric matrix of dimension 2*n.out
times p.
## see also example(ellipsoidhull) ## Robust vs. L.S. covariance matrix set.seed(143) x <- rt(200, df=3) y <- 3*x + rt(200, df=2) plot(x,y, main="non-normal data (N=200)") mtext("with classical and robust cov.matrix ellipsoids") X <- cbind(x,y) C.ls <- cov(X) ; m.ls <- colMeans(X) d2.99 <- qchisq(0.99, df = 2) lines(ellipsoidPoints(C.ls, d2.99, loc=m.ls), col="green") if(require(MASS)) { Cxy <- cov.rob(cbind(x,y)) lines(ellipsoidPoints(Cxy$cov, d2 = d2.99, loc=Cxy$center), col="red") }# MASS
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