fda.usc (version 1.1.0)

Kernel.integrate: Integrate Smoothing Kernels.

Description

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

Usage

Kernel.integrate(u,Ker=Ker.norm,a=-1)
IKer.norm(u)
IKer.cos(u)
IKer.epa(u)
IKer.tri(u)
IKer.quar(u)
IKer.unif(u)

Arguments

u

data

Ker

Type of Kernel. By default normal kernel.

a

Lower limit of integration.

Value

• res
  Returns integrate kernel.

Details

Type of integrate kernel: ll{ 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 }

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")