kernel_transform: Shifting Kernels to a Coefficient and applying a Bandwidth.
In hericks/KDE: Kernel Density Estimation

Description Usage Arguments Details Value See Also Examples

kernel_transform is shifting and applying a bandwidth to a kernel.

1	kernel_transform(kernel, sample, bandwidth, subdivisions = 1000L)

`kernel`	a kernel as S3 object of the class Kernel.
`sample`	numeric scalar; the observation.
`bandwidth`	numeric scalar; the bandwidth.
`subdivisions`	positive numeric scalar; subdivisions parameter internally passed to `integrate_primitive`.

The validation of the returned estimator as IntegrableFunction relies on the function integrate_primitive, thus the subdivisions parameter.

The transformed (shifted and scaled) kernel as valid S3 object of class Kernel.

Kernel for more information about kernels.

# shifting the gaussian kernel
shifted_gaussian <- kernel_transform(gaussian, 2, 1)
# stretching the gaussian kernel
stretched_gaussian <- kernel_transform(gaussian, 0, 2)
x <- seq(from = -5, to = 5, length.out = 1000)

plot(x, gaussian$fun(x),
     xlim=c(-5,5), ylim=c(0,1),
     main="Kernels", xlab="", ylab="",
     col="black", type="l")
lines(x, shifted_gaussian$fun(x), col="red")
lines(x, stretched_gaussian$fun(x), col="blue")
legend("topright",
       legend=c("gaussian", "shifted_gaussian","stretched_gaussian"),
       col=c("black","red", "blue"), lty=1, cex=0.8)