alkahest (version 1.3.0)

smooth_triangular: Triangular Smoothing

Description

Weighted sliding-average or triangular smoothing.

Usage

smooth_triangular(x, y, ...)
# S4 method for numeric,numeric
smooth_triangular(x, y, m = 3)
# S4 method for ANY,missing
smooth_triangular(x, m)

Value

Returns a list with two components x and y.

Arguments

x, y

A numeric vector. If y is missing, an attempt is made to interpret x in a suitable way (see grDevices::xy.coords()).

...

Currently not used.

m

An odd integer giving the window size (i.e. the number of adjacent points to be used; see window_sliding()).

Author

N. Frerebeau

Details

It replaces each point in the signal with the weighted mean of \(m\) adjacent points.

See Also

Other smoothing methods: smooth_likelihood(), smooth_loess(), smooth_rectangular(), smooth_savitzky(), smooth_whittaker()

Examples

## Simulate data with some noise
x <- seq(-4, 4, length = 100)
y <- dnorm(x) + rnorm(100, mean = 0, sd = 0.01)

## Plot spectrum
plot(x, y, type = "l", xlab = "", ylab = "")

## Rectangular smoothing
unweighted <- smooth_rectangular(x, y, m = 3)
plot(unweighted, type = "l", xlab = "", ylab = "")

## Triangular smoothing
weighted <- smooth_triangular(x, y, m = 5)
plot(weighted, type = "l", xlab = "", ylab = "")

## Loess smoothing
loess <- smooth_loess(x, y, span = 0.75)
plot(loess, type = "l", xlab = "", ylab = "")

## Savitzky–Golay filter
savitzky <- smooth_savitzky(x, y, m = 21, p = 2)
plot(savitzky, type = "l", xlab = "", ylab = "")

## Whittaker smoothing
whittaker <- smooth_whittaker(x, y, lambda = 1600, d = 2)
plot(whittaker, type = "l", xlab = "", ylab = "")