the lowess smoother span. This gives the proportion of
points in the plot which influence the smooth at each
value. Larger values give more smoothness.
spar
smoothing parameter, typically (but not necessarily) in
(0,1]. By default NULL, i.e. the value will be
automatically selected.
bass
controls the smoothness of the fitted curve. Values of
up to 10 indicate increasing smoothness.
...
optional arguments to be passed to the underlying smoothers.
Details
The functions smoothLowess, smoothSpline, smoothSupsmu
allow to smooth timeSerie object. The are interfaces to the
function lowess, supmsu. and smooth.spline in R's
stats package.
The ... arguments allow to pass optional arguments to the
underlying stats functions and tailor the smoothing process.
We refer to the manual pages of these functions for a proper setting
of these options.
Value
returns a bivariate 'timeSeries' object, the first column holds the original
time series data, the second the smoothed series.
Author(s)
The R core team for the underlying smoother functions.
Examples
## Use Close from MSFT's Price Series -
head(MSFT)
MSFT.CLOSE <- MSFT[, "Close"]
head(MSFT.CLOSE)
## Plot Original and Smoothed Series by Lowess -
MSFT.LOWESS <- smoothLowess(MSFT.CLOSE, f = 0.1)
head(MSFT.LOWESS)
plot(MSFT.LOWESS)
title(main = "Close - Lowess Smoothed")
## Plot Original and Smoothed Series by Splines -
MSFT.SPLINE <- smoothSpline(MSFT.CLOSE, spar = 0.4)
head(MSFT.SPLINE)
plot(MSFT.SPLINE)
title(main = "Close - Spline Smoothed")
## Plot Original and Smoothed Series by Supsmu -
MSFT.SUPSMU <- smoothSupsmu(MSFT.CLOSE)
head(MSFT.SUPSMU)
plot(MSFT.SUPSMU)
title(main = "Close - Spline Smoothed")