Kernel.integrate {fda.usc} | 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.
See Also
See Also as: Kernel
and integrate.
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")
[Package fda.usc version 2.1.0 Index]