ts_fil_lowess: LOWESS Smoothing

In tspredit: Time Series Prediction with Integrated Tuning

LOWESS Smoothing

Description

Locally Weighted Scatterplot Smoothing (LOWESS) fits local regressions to capture the primary trend while reducing noise and spikes.

Usage

ts_fil_lowess(f = 0.2)

Arguments

f	smoothing parameter. The larger this value, the smoother the series will be. This provides the proportion of points on the plot that influence the smoothing.

Value

A ts_fil_lowess object.

References

• W. S. Cleveland (1979). Robust locally weighted regression and smoothing scatterplots. Journal of the American Statistical Association.

Examples

# time series with noise
library(daltoolbox)
data(tsd)
tsd$y[9] <- 2*tsd$y[9]

# filter
filter <- ts_fil_lowess(f = 0.2)
filter <- fit(filter, tsd$y)
y <- transform(filter, tsd$y)

# plot
plot_ts_pred(y=tsd$y, yadj=y)

tspredit documentation built on Feb. 11, 2026, 9:08 a.m.