Data tf_depth for functional data. Currently implemented: Modified Band-2 Depth, see reference.

tf_depth(x, depth = "MBD", na.rm = TRUE, ...)

# S3 method for matrix
tf_depth(x, depth = "MBD", na.rm = TRUE, arg = unlist(find_arg(x, NULL)), ...)

# S3 method for tf
tf_depth(x, depth = "MBD", na.rm = TRUE, arg = NULL, ...)

Arguments

x

tf (or a matrix of evaluations)

depth

currently available: "MBD", i.e. modified band depth

na.rm

TRUE remove missing observations?

...

further arguments handed to the function computing the respective tf_depth.

arg

grid of evaluation points

Value

vector of tf_depth values

References

Sun, Y., Genton, M. G., & Nychka, D. W. (2012). Exact fast computation of band tf_depth for large functional datasets: How quickly can one million curves be ranked?. Stat, 1(1), 68-74. Lopez-Pintado, S. and Romo, J. (2009). On the Concept of Depth for Functional Data. Journal of the American Statistical Association, 104, 718-734.