fda.usc (version 0.9.4)

influnce.fdata: Functional influence measures

Description

Once estimated the functional regression model with scalar response, influence.fd function is used to obtain the functional influence measures.

Usage

influence.fdata(model,...)

Arguments

model

fregre.pc, fregre.basis or fregre.basis.cv object.

...

Further arguments passed to or from other methods.

Value

• Return:
• DCP
  Cook's Distance for Prediction.
• DCE
  Cook's Distance for Estimation.
• DP
  $\mbox{Pe}\tilde{\mbox{n}}\mbox{a's}$ Distance.

Details

Identify influential observations in the functional linear model in which the predictor is functional and the response is scalar. Three statistics are introduced for measuring the influence: Distance Cook Prediction DCP, Distance Cook Estimation DCE and Distance $\mbox{pe}\tilde{\mbox{n}}\mbox{a}$ DP respectively.

References

Febrero-Bande, M., Galeano, P. and Gonzalez-Manteiga, W. (2010). Measures of influence for the functional linear model with scalar response. Journal of Multivariate Analysis 101, 327-339.

See Also

See Also as: fregre.pc, fregre.basis, influence.quan

Examples

data(tecator)
x=tecator$absorp.fdata
y=tecator$y$Fat
#NO RUN
#res1=fregre.pc(x,y,1:3)  
#res.infl1=influence.fdata(res1)  
#res2=fregre.basis(x,y)  
#res.infl2=influence.fdata(res2)  

#res<-res1
#res.infl<-res.infl1
#mat=cbind(y,res$fitted.values,res.infl$DCP,res.infl$DCE,res.infl$DP)
#colnames(mat)=c("Resp.","Pred.","DCP","DCE","DP")
#pairs(mat)