Calculate L2-Depth
Calculates the L2-depth of points w.r.t. a multivariate data set.
depth.L2(x, data, mah.estimate = "moment", mah.parMcd = 0.75)
x |
Matrix of objects (numerical vector as one object) whose depth is to be calculated; each row contains a d-variate point. Should have the same dimension as |
data |
Matrix of data where each row contains a d-variate point, w.r.t. which the depth is to be calculated. |
mah.estimate |
is a character string specifying which estimates to use when calculating sample covariance matrix; can be |
mah.parMcd |
is the value of the argument |
Calculates L2-depth (Mosler, 2013). L2-depth is based on the oultyingness distance calculated as the average L2-distance from (a row of) x to each point in data.
Numerical vector of depths, one for each row in x; or one depth value if x is a numerical vector.
Mosler, K. (2013). Depth statistics. In: Becker, C., Fried, R. and Kuhnt, S. (eds), Robustness and Complex Data Structures: Festschrift in Honour of Ursula Gather, Springer-Verlag (Berlin, Heidelberg), 17–34.
depth.halfspace for calculation of the Tukey depth.
depth.Mahalanobis for calculation of Mahalanobis depth.
depth.projection for calculation of projection depth.
depth.qhpeeling for calculation of convex hull peeling depth.
depth.simplicial for calculation of simplicial depth.
depth.simplicialVolume for calculation of simplicial volume depth.
depth.spatial for calculation of spatial depth.
depth.potential for calculation of data potential.
depth.zonoid for calculation of zonoid depth.
# 5-dimensional normal distribution
data <- mvrnorm(1000, rep(0, 5),
matrix(c(1, 0, 0, 0, 0,
0, 2, 0, 0, 0,
0, 0, 3, 0, 0,
0, 0, 0, 2, 0,
0, 0, 0, 0, 1),
nrow = 5))
x <- mvrnorm(10, rep(1, 5),
matrix(c(1, 0, 0, 0, 0,
0, 1, 0, 0, 0,
0, 0, 1, 0, 0,
0, 0, 0, 1, 0,
0, 0, 0, 0, 1),
nrow = 5))
depths <- depth.spatial(x, data)
cat("Depths:", depths, "\n")Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.