frobenius_norm: Frobenius norm

In adamethods: Archetypoid Algorithms and Anomaly Detection

Description

Computes the Frobenius norm.

Usage

frobenius_norm(m)

Arguments

m	Data matrix with the residuals. This matrix has the same dimensions as the original data matrix.

Details

Residuals are vectors. If there are p variables (columns), for every observation there is a residual that there is a p-dimensional vector. If there are n observations, the residuals are an n times p matrix.

Value

Real number.

Author(s)

Guillermo Vinue, Irene Epifanio

References

Eugster, M.J.A. and Leisch, F., From Spider-Man to Hero - Archetypal Analysis in R, 2009. Journal of Statistical Software 30(8), 1-23, https://doi.org/10.18637/jss.v030.i08

Vinue, G., Epifanio, I., and Alemany, S.,Archetypoids: a new approach to define representative archetypal data, 2015. Computational Statistics and Data Analysis 87, 102-115, https://doi.org/10.1016/j.csda.2015.01.018

Vinue, G., Anthropometry: An R Package for Analysis of Anthropometric Data, 2017. Journal of Statistical Software 77(6), 1-39, https://doi.org/10.18637/jss.v077.i06

Examples

mat <- matrix(1:4, nrow = 2)
frobenius_norm(mat)
                 

adamethods documentation built on Aug. 4, 2020, 5:08 p.m.