ksmooth

From stats v3.2.5 by R-core R-core@R-project.org

Kernel Regression Smoother

The Nadaraya--Watson kernel regression estimate.

Keywords: smooth

Usage

ksmooth(x, y, kernel = c("box", "normal"), bandwidth = 0.5, range.x = range(x), n.points = max(100L, length(x)), x.points)

Arguments

x: input x values. Long vectors are supported.
y: input y values. Long vectors are supported.
kernel: the kernel to be used. Can be abbreviated.
bandwidth: the bandwidth. The kernels are scaled so that their quartiles (viewed as probability densities) are at $+/-$ 0.25*bandwidth.
range.x: the range of points to be covered in the output.
n.points: the number of points at which to evaluate the fit.
x.points: points at which to evaluate the smoothed fit. If missing, n.points are chosen uniformly to cover range.x. Long vectors are supported.

Value

x: values at which the smoothed fit is evaluated. Guaranteed to be in increasing order.
y: fitted values corresponding to x.

Note

This function was implemented for compatibility with S, although it is nowhere near as slow as the S function. Better kernel smoothers are available in other packages such as \href{https://CRAN.R-project.org/package=#1}{\pkg{#1}}KernSmoothKernSmooth.

Examples

library(stats)

require(graphics)

with(cars, {
    plot(speed, dist)
    lines(ksmooth(speed, dist, "normal", bandwidth = 2), col = 2)
    lines(ksmooth(speed, dist, "normal", bandwidth = 5), col = 3)
})

Documentation reproduced from package stats, version 3.2.5, License: Part of R 3.2.5

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