band_depth: Compute the band depth for a sample of curves/observations.

In fdaoutlier: Outlier Detection Tools for Functional Data Analysis

Compute the band depth for a sample of curves/observations.

Description

This function computes the band depth of López-Pintado and Romo (2009) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1198/jasa.2009.0108")}. Bands of 2 functions are always considered using the fast algorithm of Sun et al. (2012) \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1002/sta4.8")}.

Usage

band_depth(dt)

Arguments

dt	A matrix or data frame of size n observations/curves by p domain/evaluation points.

Value

A numeric vector of size nrow(dt) containing the band depth values of each curve.

References

López-Pintado, S., & Romo, J. (2009). On the Concept of Depth for Functional Data. Journal of the American Statistical Association, 104(486), 718-734.

Sun, Y., Genton, M. G., & Nychka, D. W. (2012). Exact fast computation of band depth for large functional datasets: How quickly can one million curves be ranked?. Stat, 1(1), 68-74.

Examples

dt1 <- simulation_model1()
bd2 <- band_depth(dt = dt1$data)

fdaoutlier documentation built on Oct. 1, 2023, 1:06 a.m.