archetypoids_norm_frob {adamethods} | R Documentation |
Archetypoid algorithm with the Frobenius norm
Description
This function is the same as archetypoids
but the 2-norm
is replaced by the Frobenius norm. Thus, the comparison with the robust archetypoids
can be directly made.
Usage
archetypoids_norm_frob(numArchoid, data, huge = 200, ArchObj)
Arguments
numArchoid |
Number of archetypoids. |
data |
Data matrix. Each row corresponds to an observation and each column corresponds to a variable. All variables are numeric. |
huge |
Penalization added to solve the convex least squares problems. |
ArchObj |
The list object returned by the
|
Value
A list with the following elements:
cases: Final vector of archetypoids.
rss: Residual sum of squares corresponding to the final vector of archetypoids.
archet_ini: Vector of initial archetypoids.
alphas: Alpha coefficients for the final vector of archetypoids.
resid: Matrix with the residuals.
Author(s)
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
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
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
See Also
Examples
data(mtcars)
data <- mtcars
k <- 3
numRep <- 2
huge <- 200
lass <- stepArchetypesRawData_norm_frob(data = data, numArch = k,
numRep = numRep, verbose = FALSE)
res <- archetypoids_norm_frob(k, data, huge, ArchObj = lass)
str(res)
res$cases
res$rss