frobenius_norm_funct_multiv_robust {adamethods} | R Documentation |
Computes the functional multivariate robust Frobenius norm.
frobenius_norm_funct_multiv_robust(m, PM, prob, nbasis, nvars)
m |
Data matrix with the residuals. This matrix has the same dimensions as the original data matrix. |
PM |
Penalty matrix obtained with |
prob |
Probability with values in [0,1]. |
nbasis |
Number of basis. |
nvars |
Number of variables. |
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.
Real number.
Irene Epifanio
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
mat <- matrix(1:400, ncol = 20) PM <- matrix(1:100, ncol = 10) frobenius_norm_funct_multiv_robust(mat, PM, 0.8, 10, 2)