stepArchetypesRawData {Anthropometry} | R Documentation |
Archetype algorithm to raw data
Description
This is a slight modification of the original stepArchetypes
function of the archetypes R package to apply the archetype algorithm to raw data. The stepArchetypes
function standardizes the data by default and this option is not always desired.
Usage
stepArchetypesRawData(data,numArch,numRep=3,verbose=TRUE)
Arguments
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. |
Value
A list with numArch
elements. Each element is a list of class attribute stepArchetypes
with numRep
elements.
Author(s)
Guillermo Vinue based on the the original stepArchetypes
function of archetypes.
References
Eugster, M. J., and Leisch, F., (2009). From Spider-Man to Hero - Archetypal Analysis in R, Journal of Statistical Software 30, 1–23, doi: 10.18637/jss.v030.i08.
Vinue, G., Epifanio, I., and Alemany, S., (2015). Archetypoids: a new approach to define representative archetypal data, Computational Statistics and Data Analysis 87, 102–115.
See Also
Examples
#COCKPIT DESIGN PROBLEM:
#As a toy example, only the first 25 individuals are used.
USAFSurvey_First25 <- USAFSurvey[1:25, ]
#Variable selection:
variabl_sel <- c(48, 40, 39, 33, 34, 36)
#Changing to inches:
USAFSurvey_First25_inch <- USAFSurvey_First25[,variabl_sel] / (10 * 2.54)
#Data preprocessing:
USAFSurvey_preproc <- preprocessing(USAFSurvey_First25_inch, TRUE, 0.95, TRUE)
#For reproducing results, seed for randomness:
#suppressWarnings(RNGversion("3.5.0"))
#set.seed(2010)
#Run archetype algorithm repeatedly from 1 to numArch archetypes:
#This is a toy example. In other situation, choose numArch=10 and numRep=20.
numArch <- 5 ; numRep <- 2
lass <- stepArchetypesRawData(data = USAFSurvey_preproc$data, numArch = 1:numArch,
numRep = numRep, verbose = FALSE)
#To understand the warning messages, see the vignette of the
#archetypes package.