Integrate Smoothing Kernels.
Represent integrate kernels: normal, cosine, triweight, quartic and uniform.
Kernel.integrate(u, Ker = Ker.norm, a = -1)
u |
data |
Ker |
Type of Kernel. By default normal kernel. |
a |
Lower limit of integration. |
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
|
|
Returns integrate kernel.
Manuel Febrero-Bande, Manuel Oviedo de la Fuente manuel.oviedo@usc.es
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.
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")
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.