How to get rid of multiple outliers in a timeseries in R? -

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i'm using "outliers" package in order remove undesirable values. seems rm.outliers() funcion not replace outliers @ same time. probably, rm.outliers() not perform despikes recursively. then, have call function lot of times in order replace outliers. here reproducible example of issue i'm experiencing:

require(outliers)    # creating timeseries:    set.seed(12345)    y = rnorm(10000)    # inserting outliers:    y[4000:4500] = -11    y[4501:5000] = -10    y[5001:5100] = -9    y[5101:5200] = -8    y[5201:5300] = -7    y[5301:5400] = -6    y[5401:5500] = -5 # plotting timeseries + outliers: plot(y, type="l", col="black", lwd=6, xlab="time", ylab="w'") # trying rid of outliers replacing them series mean value: new.y = outliers::rm.outlier(y, fill=true, median=false) new.y = outliers::rm.outlier(new.y, fill=true, median=false) # plotting new timeseries "after removing outliers": lines(new.y, col="red") # inserting legend: legend("bottomleft", c("raw", "new series"), col=c("black","red"), lty=c(1,1), horiz=false, bty="n")

does know how improve code above, outliers replaced mean value?

best thought come use for loop, keeping track of outliers find them.

plot(y, type="l", col="black", lwd=6, xlab="time", ylab="w'")  maxiter <- 100 outlierq <- rep(f, length(y))  (i in 1:maxiter) {   bad <- outlier(y, logical = t)   if (!any(bad)) break   outlierq[bad] <- t   y[bad] <- mean(y[!bad]) }  y[outlierq] <- mean(y[!outlierq])  lines(y, col="blue")

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