Kernel.integrate: Integrate Smoothing Kernels.
In fda.usc: Functional Data Analysis and Utilities for Statistical Computing

Kernel.integrate

R Documentation

Integrate Smoothing Kernels.

Description

Represent integrate kernels: normal, cosine, triweight, quartic and uniform.

Usage

Kernel.integrate(u, Ker = Ker.norm, a = -1)

Arguments

`u`	data
`Ker`	Type of Kernel. By default normal kernel.
`a`	Lower limit of integration.

Details

Type of integrate kernel:

	Integrate Normal Kernel: `IKer.norm`
	Integrate Cosine Kernel: `IKer.cos`
	Integrate Epanechnikov Kernel: `IKer.epa`
	Integrate Triweight Kernel: `IKer.tri`
	Integrate Quartic Kernel: `IKer.quar`
	Integrate Uniform Kernel: `IKer.unif`

Value

Returns integrate kernel.

Author(s)

Manuel Febrero-Bande, Manuel Oviedo de la Fuente manuel.oviedo@udc.es

References

Ferraty, F. and Vieu, P. (2006). Nonparametric functional data analysis. Springer Series in Statistics, New York.

Hardle, W. Applied Nonparametric Regression. Cambridge University Press, 1994.

Examples

y=qnorm(seq(.1,.9,len=100))
d=IKer.tri(y)
e=IKer.cos(y)
e2=Kernel.integrate(u=y,Ker=Ker.cos)
e-e2
f=IKer.epa(y)
f2=Kernel.integrate(u=y,Ker=Ker.epa)
f-f2
plot(d,type="l",ylab="Integrate Kernel")
lines(e,col=2,type="l")
lines(f,col=4,type="l")

fda.usc documentation built on Oct. 17, 2022, 9:06 a.m.