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Elastic Depth for Functional Data

Source: R/alignment.R
elastic.depth.Rd

Compute elastic depth scores that decompose into amplitude and phase components. Elastic depth measures the centrality of each curve relative to the sample, accounting for both vertical variation (amplitude) and horizontal variation (phase/warping).

Usage

elastic.depth(fdataobj, lambda = 0)

Arguments

fdataobj

An object of class 'fdata'.

lambda

Regularisation parameter controlling warping smoothness (default 0).

Value

An object of class 'elastic.depth' with components:

amplitude_depth

numeric vector of amplitude depth scores

phase_depth

numeric vector of phase depth scores

combined_depth

numeric vector of combined depth scores

References

Lopez-Pintado, S. and Romo, J. (2009). On the concept of depth for functional data. Journal of the American Statistical Association, 104(486):718–734.

Srivastava, A. and Klassen, E. (2016). Functional and Shape Data Analysis. Springer.

See also

elastic.outlier.detection

Examples

# \donttest{
set.seed(1)
t <- seq(0, 1, length.out = 50)
X <- matrix(0, 15, 50)
for (i in 1:15) X[i, ] <- sin(2 * pi * t + runif(1, -0.3, 0.3))
fd <- fdata(X, argvals = t)
ed <- elastic.depth(fd)
# }