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Lp Metric for Functional Data

Source: R/irregFdata.R, R/metric.R
metric.lp.Rd

Computes the Lp distance between functional data objects using numerical integration (Simpson's rule). Works with both regular fdata and irregular irregFdata objects.

Usage

# S3 method for class 'irregFdata'
metric.lp(x, p = 2, ...)

metric.lp(x, ...)

# S3 method for class 'fdata'
metric.lp(x, y = NULL, p = 2, w = 1, ...)

Arguments

x

A functional data object (fdata or irregFdata).

p

The order of the Lp metric (default 2 for L2 distance).

...

Additional arguments passed to methods.

y

An object of class 'fdata'. If NULL, computes self-distances for x (more efficient symmetric computation). Only supported for fdata.

w

Optional weight vector of length equal to number of evaluation points. Default is uniform weighting. Only supported for fdata.

Value

A distance matrix.

Examples

# Regular fdata
fd <- fdata(matrix(rnorm(100), 10, 10))
D <- metric.lp(fd)  # Self-distances

# Irregular fdata
ifd <- sparsify(fd, minObs = 3, maxObs = 7, seed = 42)
D_irreg <- metric.lp(ifd)