# Kernel.asymmetric

0th

Percentile

##### Asymmetric Smoothing Kernel

Represent Asymmetric Smoothing Kernels: normal, cosine, triweight, quartic and uniform.

 AKer.norm=ifelse(u>=0,2*dnorm(u),0) AKer.cos=ifelse(u>=0,pi/2*(cos(pi*u/2)),0) AKer.epa=ifelse(u>=0 & u<=1,3/2*(1-u^2),0) AKer.tri=ifelse(u>=0 & u<=1,35/16*(1-u^2)^3,0) AKer.quar=ifelse(u>=0 & u<=1,15/8*(1-u^2)^2,0) AKer.unif=ifelse(u>=0 & u<=1,1,0)

Keywords
Kernel
##### Usage
Kernel.asymmetric(u, type.Ker = "AKer.norm")
##### Arguments
u

Data.

type.Ker

Type of asymmetric metric kernel, by default asymmetric normal kernel.

##### Details

Type of Asymmetric kernel:

 Asymmetric Normal Kernel: AKer.norm Asymmetric Cosine Kernel: AKer.cos Asymmetric Epanechnikov Kernel: AKer.epa Asymmetric Triweight Kernel: AKer.tri Asymmetric Quartic Kernel: AKer.quar Asymmetric Uniform Kernel: AKer.unif

##### Value

Returns asymmetric kernel.

##### 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.

##### Aliases
• Kernel.asymmetric
• AKer.norm
• AKer.cos
• AKer.epa
• AKer.tri
• AKer.quar
• AKer.unif
##### Examples
# NOT RUN {
y=qnorm(seq(.1,.9,len=100))
a<-Kernel.asymmetric(u=y)
b<-Kernel.asymmetric(type.Ker="AKer.tri",u=y)
c=AKer.cos(y)
# }

Documentation reproduced from package fda.usc, version 2.0.2, License: GPL-2

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