ILS (version 0.1.0)

QuantileDepth: Creates a 'lab.fqcs' object to estimate functional quantiles using data depth procedures.

Description

It defines a lab.fqcs object to estimate functional quantiles using data depth procedures (Lopez-Pintado and Romo, 2009). The required functional quantiles are obtained from data depths values of each curve. If quantile argument is 0.9, 0.95 and 0.05 functional quantiles are obtained.

Usage

QuantileDepth(x, quantile = 0.95)

Arguments

x

Object of type fdata

quantile

Probability defined in the interval [0,1]

References

Febrero-Bande, M. and Oviedo, M. (2012), "Statistical computing in functional data analysis: the R package fda.usc". Journal of Statistical Software 51 (4), 1-28.

Lopez-Pintado, S. and Romo, J. (2009), "On the concept of depth for functional data", Journal of the American Statistical Association, 104, 486-503.

Examples

## Not run: 
# library(ILS)
# data(TG)
# delta <- seq(from = 40 ,to = 850 ,length.out = 1000 )
# curves.fqcd <- lab.fqcd(TG, argvals = delta)
# n <- curves.fqcd$n
# m <- curves.fqcd$m
# p <- curves.fqcd$p
# curves.all <- TG[,,1]
# for(i in 2:p) curves.all <- rbind(curves.all,TG[,,i])
# curves.fdata <- fdata(mdata = curves.all,delta)
# qd <- QuantileDepth(curves.fdata)
# windows(20,10)
# par(mfrow=c(1,2))
# plot(qd, main="Quantiles of TG curves (95%)",col=c("red","blue"),lwd=2,legend = FALSE)
# legend(50,80,c("Quantile 2.5%","Quantile 97.5%"),
#       col=c("red","blue"),lty=c(1,1),lwd=1,cex=0.7)
# plot(curves.fdata,main="Quantiles of TG curves (95%)",col="gray")
# for(i in 1:2)
# lines(qd[[i]],col="red",lty = 2,lwd = 2)
# legend(50,80,c("Quantiles","TG Curves (105)"),
#       col=c("red","gray"),lty=c(1,2),lwd=2,cex=0.7)
# par(mfrow=c(1,1))
# ## End(Not run)