Nothing
`quantile_outliers_trim` <- function(data, dfunc = depth.RP, trim = 0.1, nb = 200, suav = 0.05, ...)
{
functions = t(data$y)
n <- dim(functions)[1]
m <- dim(functions)[2]
if(is.null(n) && is.null(m))
stop("I do not have a matrix")
d = dfunc(data,...)$prof
rid <- rank(d, ties.method = "first")
num.boot <- floor(trim * n)
sample.trim <- functions[rid >= num.boot,]
cuantiles <- numeric(nb)
vv = var(functions)
for(i in 1:nb){
bsample <- sample.trim[sample(1:(n-num.boot), size = n, replace = T),]
if(suav>0){
bsample <- bsample + mvrnorm(n = n, rep(0, m), vv * suav)
}
bsample = fts(1:dim(bsample)[1], bsample)
d = dfunc(bsample,...)$prof
cuantiles[i] <- quantile(d, probs = 0.01, type = 8)
}
return(cuantiles)
}
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