| kernel.assign {DCSmooth} | R Documentation |
Assign a Kernel Function
Description
Assign a Kernel Function
Usage
kernel.assign(kernel_id)
Arguments
kernel_id |
a string specifying the kernel identifier as given in the details. |
Value
kernel.assign returns an object of class "function". This
function takes two arguments, a numeric vector in the first argument and a
single number in the second. The function itself will return a matrix with
one column and the same number of rows as the input vector.
Details
kernel.assign sets a pointer to a specified kernel function available
in the DCSmooth package. The kernels are boundary kernels of the form
K(u,q), where u \in [-1, q] and q \in [0, 1]
q = [0, 1]. Kernels are of the Müller-Wang type ("MW"), Müller type ("M")
or truncated kernels ("TR").
References
Müller, H.-G. and Wang, J.-L. (1994). Hazard rate estimation under random censoring with varying kernels and bandwidths. Biometrics, 50:61-76.
Müller, H.-G. (1991). Smooth optimum kernel estimators near endpoints. Biometrika, 78:521-530.
Feng, Y. and Schäfer B. (2021). Boundary Modification in Local Regression. Working Papers CIE 144, Paderborn University.
See Also
Examples
# See vignette("DCSmooth") for further examples and explanation
u <- seq(from = -1, to = 0.5, length.out = 151)
kern_MW220 <- kernel.assign("MW_220")
k <- kern_MW220(u, 0.5)
plot(u, k, type = "l")