Description Usage Arguments Value References See Also Examples
Provides depth-based multivariate central or semi-space nonparametric tolerance regions. These can be calculated for any continuous multivariate data set. Either (P, 1-alpha) tolerance regions or beta-expectation tolerance regions can be specified.
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x |
An |
alpha |
The level chosen such that |
P |
The proportion of the population to be covered by this tolerance interval. Note that if a (P, 1-alpha) tolerance region is required, then both |
Beta |
The confidence level for a beta-expectation tolerance region. Note that if a beta-expectation tolerance region is required, then |
depth.fn |
The data depth function used to perform the ordering of the multivariate data. Thus function must be coded in such a way that the first argument is multivariate data for which to calculate the depth values and the second argument is the original multivariate sample, |
adjust |
Whether an adjustment should be made during an intermediate calculation for determining the number of points that need to be included in the multivariate region. If |
type |
The type of multivariate hyperrectangular region to calculate. If |
semi.order |
If |
L |
If |
U |
If |
... |
Additional arguments passed to the |
npmvtol.region
returns a p
x2
matrix where the columns give the lower and upper limits, respectively, of the multivariate hyperrectangular tolerance region.
Young, D. S. and Mathew, T. (2020+), Nonparametric Hyperrectangular Tolerance and Prediction Regions for Setting Multivariate Reference Regions in Laboratory Medicine, Submitted.
distfree.est
, mvtol.region
, npregtol.int
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## 90%/95% semi-space tolerance region for a sample
## of size 20 generated from a multivariate normal
## distribution. The mdepth function below is not
## a true depth function, but used only for
## illustrative purposes.
mdepth <- function(pts, x){
mahalanobis(pts, center = rep(0, 3),
cov = diag(1, 3))
}
set.seed(100)
x <- cbind(rnorm(100), rnorm(100), rnorm(100))
out <-npmvtol.region(x = x, alpha = 0.10, P = 0.95, depth.fn = mdepth,
type = "semispace", semi.order = list(lower = 2,
center = 3, upper = 1))
out
|
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