Whittaker Smoothing

Whittaker Smoothing

Usage

smooth_whittaker(x, y, ...)

# S4 method for class 'numeric,numeric'
smooth_whittaker(x, y, lambda = 1600, d = 2, sparse = FALSE)

# S4 method for class 'ANY,missing'
smooth_whittaker(x, lambda = 1600, d = 2, sparse = FALSE)

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.

lambda

An integer giving the smoothing parameter. The larger lambda is, the smoother the curve.

d

An integer specifying the order of the penalty.

sparse

A logical scalar: should sparse matrices be used for computation? If TRUE, Matrix is required.

Value

Returns a list with two components x and y.

References

Eilers, P. H. C. (2003). A Perfect Smoother. Analytical Chemistry, 75(14): 3631-36. doi:10.1021/ac034173t .

See also

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

Author

N. Frerebeau

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 = "")