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\name{depthf.}
\alias{depthf.}
\title{
Calculate Functional Depth
}
\description{
Calculates the depth of functions w.r.t. a functional data set.
The detailed descriptions are found in the corresponding topics.
}
\usage{
depthf.(datafA, datafB, notion, ...)
## Adjusted band depth
# depthf.ABD(datafA, datafB, range = NULL, d = 101, norm = c("C", "L2"),
# J = 2, K = 1)
## Band depth
# depthf.BD(datafA, datafB, range = NULL, d = 101)
## Univariate integrated and infimal depth
# depthf.fd1(datafA, datafB, range = NULL, d = 101, order = 1, approx = 0)
## Bivariate integrated and infimal depth
# depthf.fd2(datafA, datafB, range = NULL, d = 101)
## h-mode depth
# depthf.hM(datafA, datafB, range = NULL, d = 101, norm = c("C", "L2"),
# q = 0.2)
## Bivariate h-mode depth
# depthf.hM2(datafA, datafB, range = NULL, d = 101, q = 0.2)
## Half-region depth
# depthf.HR(datafA, datafB, range = NULL, d = 101)
## Univariate random projection depths
# depthf.RP1(datafA, datafB, range = NULL, d = 101, nproj = 50, nproj2 = 5)
# Bivariate random projection depths
# depthf.RP2(datafA, datafB, range = NULL, d = 101, nproj = 51)
}
\arguments{
\item{datafA}{
Functions whose depth is computed, represented by a \code{dataf} object of their arguments
and functional values.
}
\item{datafB}{
Random sample functions with respect to which the depth of \code{datafA} is computed.
\code{datafB} is represented by a \code{dataf} object of their arguments
and functional values.
}
\item{notion}{
The name of the depth notion (shall also work with a user-defined depth function named \code{"depthf.<name>"}).
}
\item{\dots}{
Additional parameters passed to the depth functions.
}
}
\seealso{
\code{\link{depthf.ABD}}
\code{\link{depthf.BD}}
\code{\link{depthf.fd1}}
\code{\link{depthf.fd2}}
\code{\link{depthf.hM}}
\code{\link{depthf.hM2}}
\code{\link{depthf.HR}}
\code{\link{depthf.RP1}}
\code{\link{depthf.RP2}}
}
\value{
Numerical vector of depths, one for each function in \code{datafA}; or one depth value if \code{datafA} is a single function.
}
\examples{
# real data example
datafA = dataf.population()$dataf[1:20]
datafB = dataf.population()$dataf[21:50]
depthf.(datafA, datafB, notion = "HR")
dataf2A = derivatives.est(datafA,deriv=c(0,1))
dataf2B = derivatives.est(datafB,deriv=c(0,1))
depthf.(dataf2A, dataf2B, notion = "fd2")
}
\keyword{ robust }
\keyword{ functional }
\keyword{ nonparametric }
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