fda.usc (version 0.9.4)

depth.mode: Provides the depth measure (mode) for functional data

Description

The depth.mode function implements the modal depth that select the curve most densely surrounded by others as the deepest one. By default, the distance is calculated using metric.lp function.

Usage

depth.mode(fdataobj,trim=0.25,metric=metric.lp,h=0.15,scale=TRUE,
draw=FALSE,...)

Arguments

fdataobj

fdata class object.

trim

The alpha of the trimming.

h

Bandwidth, h>0.

metric

Metric function, by default metric.lp.

scale

=TRUE, scale the matrix, see scale.

draw

=TRUE, draw the curves, the sample median and trimmed mean.

...

Further arguments passed to or from other methods.

Value

• median
  Deepest curve.
• lmed
  Index deepest element median.
• mtrim
  code{fdata} class object with the average from the ((1-trim)% deepest curves.
• ltrim
  Index of curves with trimmed mean mtrim.
• dep
  Depth of each curve.
• dep
  Depth of each curve.
• dist
  Distance matrix between curves or functional data.

Details

The mode of a functional data will be the deepest curve.

References

Cuevas, A.; Febrero-Bande, M. and Fraiman, R. (2007). Robust estimation and classification for functional data via projection-based depth notions. Computational Statistics 22, 3, 481{-}496. Febrero, M., Galeano, P., and Gonzalez-Manteiga, W. (2008). Outlier detection in functional data by depth measures with application to identify abnormal NOx levels. Environmetrics 19, 4, 331{-}345. Cuevas A, Febrero M, Fraiman R. 2006. On the use of bootstrap for estimating functions with functional data. Computational Statistics and Data Analysis 51: 1063{-}1074.

See Also

See Also as depth.FM, depth.RP, and depth.RPD.

Examples

#Ex: CanadianWeather data
t=1:365
fdataobj<-fdata(t(CanadianWeather$dailyAv[,,1]),t)
#Modal Depth
out.mode=depth.mode(fdataobj)
out.mode2=depth.mode(fdataobj,trim=0.10,draw=TRUE)
out.mode3=depth.mode(fdataobj,metriC=semimetric.basis, draw=TRUE)
out.mode4=depth.mode(fdataobj,h=0.05, draw=TRUE)
plot(out.mode$mtrim)
lines(out.mode2$mtrim,col=2)
lines(out.mode3$mtrim,col=3)
lines(out.mode4$mtrim,col=4)