Nothing
#################################################################
## Monte Carlo analysis of CIP
montecarlo <- function(input, ...) UseMethod("montecarlo")
montecarlo.compind <- function(input, nboot = 250, random=NULL) {
if(is.null(random))
stop('random can not be null, should be the paramenters to vary in MonteCarlo')
possible.randoms <- c("aggregation", "normalization", "missingindicator", "cleaning")
final.random <- random[random %in% possible.randoms]
if((length(final.random) == 0) && (typeof(final.random) == "character"))
stop('random can only be only among aggregation, normalization, missingindicator and cleaning')
ctr <- input$ctr
if (missing(input))
stop('Calculated index of class compind is missing')
entity = rownames(input$index)
nentity = length(entity)
indexMC = matrix(data = NA, nrow = nentity, ncol = nboot)
rankingMC = matrix(data = NA, nrow = nentity, ncol = nboot)
for (m in 1 : nboot) {
dft = list(aggregation = c('geometric' , 'linear'),
normalization = c('min-max', 'none', 'z-score', 'robust-z-score'),
missingindicator = c('last','none','reweight', 'linear'),
cleaning = c('none', 'hampel_twosided' , 'hampel_onesided')
)
rndctr = ctr
# randomize aggregation
if ('aggregation'%in%final.random){
rndctr$aggregation = dft$aggregation[sample(1:length(dft$aggregation), 1)]
}
# randomize normalization
if ('normalization'%in%final.random){
rndctr$normalization = dft$normalization[sample(1:length(dft$normalization), 1)]
}
# randomize missing data technique
if ('missingindicator'%in%final.random){
rndctr$missingindicator = dft$missingindicator[sample(1:length(dft$missingindicator), 1)]
}
# randomize cleaning
if ('cleaning'%in%final.random){
rndctr$cleaning = dft$cleaning[sample(1:length(dft$cleaning), 1)]
}
# complete the dataset if randomization on missing data technique
call <- input$call
call$ctr <- rndctr
tmp = eval(call)
indexMC[,m] = tmp$index
rankingMC[,m] = tmp$ranking
}
dimnames(indexMC) = dimnames(rankingMC) = list(entity = entity, 1:nboot)
out=list(index = input, indexMC = indexMC, rankingMC = rankingMC)
out$call <- match.call()
class(out) <- "montecarlo"
return(out)
}
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