Archetype algorithm to raw data with the robust Frobenius norm
This is a slight modification of stepArchetypesRawData
to use the archetype algorithm with the robust Frobenius norm.
stepArchetypesRawData_robust(data, numArch, numRep = 3,
verbose = TRUE, saveHistory = FALSE, prob)data |
Data to obtain archetypes. |
numArch |
Number of archetypes to compute, from 1 to |
numRep |
For each |
verbose |
If TRUE, the progress during execution is shown. |
saveHistory |
Save execution steps. |
prob |
Probability with values in [0,1]. |
A list with the archetypes.
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
data(mtcars)
data <- as.matrix(mtcars)
numArch <- 5
numRep <- 2
lass <- stepArchetypesRawData_robust(data = data, numArch = 1:numArch,
numRep = numRep, verbose = FALSE,
saveHistory = FALSE, prob = 0.8)
str(lass)
length(lass[[1]])
class(lass[[1]])Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.