Skip to content
/ dbFDA Public

Depth-based methods for functional data analysis.

Notifications You must be signed in to change notification settings

aefdz/dbFDA

Repository files navigation

License

Depth-based prediction bands for functional data

Enveloping without prediction or forecasting

focal <- '1'
dist <- 'l2' # dist<-'supremum'
plotting <- TRUE 

resultsBand <- banddpeeling(data, focal, dist, plotting)

## Press <Enter> to continue...

## Press <Enter> to continue...

## Press <Enter> to continue...

## Press <Enter> to continue...
resultsBand #Envelope 
## $subsample
##  [1] "1"  "43" "29" "84" "22" "88" "28" "52" "63" "15" "41" "86" "97" "4"  "46"
## [16] "79" "14" "10"

Curve Extension

cut <- 25 # number of points observed of the partially observed function
kcurves <- 10 # number of curves of the envelope involved in the band

results <- extension(data, focal, cut, dist)

pl <- plotBand(data, cut, results$Jordered, kcurves, focal)

To explore different values of cut and kcurves (only running in Rstudio)

manipulate(
  {
  plotBand(data, cut, results$Jordered, kcurves, focal)
  },
  kcurves = slider(min = 1, max = length(results$Jordered), step = 1, ticks = TRUE),
  cut = slider(1, 99, initial = 50, step = 1)
)

About

Depth-based methods for functional data analysis.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages