Last data update: 2014.03.03
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R: Asymmetric Smoothing Kernel
Kernel.asymmetric | R Documentation |
Asymmetric Smoothing Kernel
Description
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) |
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Usage
Kernel.asymmetric(u,type.Ker="AKer.norm")
AKer.norm(u)
AKer.cos(u)
AKer.epa(u)
AKer.tri(u)
AKer.quar(u)
AKer.unif(u)
Arguments
type.Ker |
Type of asymmetric metric kernel, by default asymmetric normal kernel.
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u |
Data.
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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 |
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Value
res |
Returns asymmetric kernel.
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Author(s)
Manuel Febrero-Bande, Manuel Oviedo de la Fuente manuel.oviedo@usc.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))
a<-Kernel.asymmetric(u=y)
b<-Kernel.asymmetric(type.Ker="AKer.tri",u=y)
c=AKer.cos(y)
Results
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