adamethods (version 1.2.1)

frobenius_norm_robust: Robust Frobenius norm

Description

Computes the robust Frobenius norm.

Usage

frobenius_norm_robust(m, prob)

Arguments

m

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

prob

Probability with values in [0,1].

Value

Real number.

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.

References

Moliner, J. and Epifanio, I., Robust multivariate and functional archetypal analysis with application to financial time series analysis, 2019. Physica A: Statistical Mechanics and its Applications 519, 195-208. https://doi.org/10.1016/j.physa.2018.12.036

Examples

# NOT RUN {
mat <- matrix(1:4, nrow = 2)
frobenius_norm_robust(mat, 0.8)
                 
# }