runmean function

Running Interval Smoother

The runmean implements a running interval smoother on the trimmed mean, rungen uses general M-estimators, runmbo performs interval smoothing on M-estimators with bagging.

runmean(x, y, fr = 1, tr = 0.2, ...)
rungen(x, y, fr = 1, est = "mom", ...)
runmbo(x, y, fr = 1, est = "mom", nboot = 40, ...)

Arguments

• x: a numeric vector of data values (predictor)
• y: a numeric vector of data values (response)
• fr: smoothing factor (see details)
• tr: trim level for the mean
• est: type of M-estimator ("mom", "onestep", or "median")
• nboot: number of bootstrap samples
• ...: currently ignored.

Details

The larger the smoothing factor, the stronger the smoothing. Often the choice fr = 1 gives good results; the general strategy is to find the smallest constant so that the plot looks reasonably smooth.

Returns

Returns the fitted values.

References

Wilcox, R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Elsevier.

See Also

ancova

Examples

## trimmed mean smoother
fitmean <- runmean(Pygmalion$Pretest, Pygmalion$Posttest)
## MOM smoother
fitmest <- rungen(Pygmalion$Pretest, Pygmalion$Posttest)
## median smoother
fitmed <- rungen(Pygmalion$Pretest, Pygmalion$Posttest, est = "median")
## bagged onestep smoother
fitbag <- runmbo(Pygmalion$Pretest, Pygmalion$Posttest, est = "onestep")

## plot smoothers
plot(Pygmalion$Pretest, Pygmalion$Posttest, col = "gray", xlab = "Pretest", ylab = "Posttest",
     main = "Pygmalion Smoothing")
orderx <- order(Pygmalion$Pretest)
lines(Pygmalion$Pretest[orderx], fitmean[orderx], lwd = 2)
lines(Pygmalion$Pretest[orderx], fitmest[orderx], lwd = 2, col = 2)
lines(Pygmalion$Pretest[orderx], fitmed[orderx], lwd = 2, col = 3)
lines(Pygmalion$Pretest[orderx], fitbag[orderx], lwd = 2, col = 4)
legend("topleft", legend = c("Trimmed Mean", "MOM", "Median", "Bagged Onestep"), col = 1:4, lty = 1)