Summarizes information from fregre.fd objects.
Summary function for fregre.pc
, fregre.basis
,
fregre.pls
, fregre.np
and
fregre.plm
functions.
Shows:
-Call. | |
-R squared. | |
-Residual variance. | |
-Index of possible atypical curves or possible outliers. | |
-Index of possible influence curves. | |
If the
fregre.fd
object comes from the fregre.pc
then shows:
-Variability of explicative variables explained by Principal Components. | |
-Variability for each principal components -PC-. | |
If draw=TRUE plot:
-y vs y fitted values. | |
-Residuals vs fitted values. | |
-Standarized residuals vs fitted values. | |
-Levarage. | |
-Residual boxplot. | |
-Quantile-Quantile Plot (qqnorm). | |
If ask
=FALSE draw graphs in
one window, by default. If ask
=TRUE, draw each graph in a window,
waiting to confirm.
## S3 method for class 'fregre.fd' summary(object, times.influ = 3, times.sigma = 3, draw = TRUE, ...)
object |
Estimated by functional regression, |
times.influ |
Limit for detect possible infuence curves. |
times.sigma |
Limit for detect possible oultiers or atypical curves. |
draw |
=TRUE draw estimation and residuals graphics. |
... |
Further arguments passed to or from other methods. |
Influence Vector of influence measures.
i.influence Index of possible influence curves.
i.atypical Index of possible atypical curves or possible outliers.
Manuel Febrero-Bande and Manuel Oviedo de la Fuente manuel.oviedo@usc.es
Summary function for fregre.pc
,
fregre.basis
, fregre.pls
, fregre.np
and fregre.plm
.
## Not run: # Ex 1. Simulated data n= 200;tt= seq(0,1,len=101) x0<-rproc2fdata(n,tt,sigma="wiener") x1<-rproc2fdata(n,tt,sigma=0.1) x<-x0*3+x1 beta = tt*sin(2*pi*tt)^2 fbeta = fdata(beta,tt) y<-inprod.fdata(x,fbeta)+rnorm(n,sd=0.1) # Functional regression res=fregre.pc(x,y,l=c(1:5)) summary(res,3,ask=TRUE) res2=fregre.pls(x,y,l=c(1:4)) summary(res2) res3=fregre.pls(x,y) summary(res3) ## End(Not run)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.