# R/cumfd.R In fda: Functional Data Analysis

#### Documented in cumfd

cumfd <- function(xrnd, xrng, nbreaks=7, nfine=101) {
#  Compute cdf_fd over a closed interval using smooth.morph.
#  Only the values of x within the interior of xrng are used
#  in order to avoid distortion due to boundary inflation.
#  Arguments:
#  xrnd    ... A vector of variable values (unsorted)
#  xrng    ... A vector of length 2 containing the boundary values.
#  Wnbasis ... Number of basis functions used by smooth.morph.
#  Snbasis ... Number of basis functions used by smooth.basis.
#  nfine   ... Length of vector of equally spaced values spanning xrng.

#  check that values of x are within xrng

if (min(xrnd) < xrng[1] || max(xrnd) > xrng[2])
stop("Values of x outside of xrng.")

#  sort the data and set up probability values

xsort  <- sort(xrnd[xrnd > xrng[1] & xrnd < xrng[2]])
N      <- length(xsort)
prbvec <- (1:N)/(N+1)

pmesh <- c(0, prbvec, 1)
xmesh <- c(xrng[1], xsort,  xrng[2])

#  set up fdPar object for smooth.morph

index = c(1, round(N*2:(nbreaks-1)/nbreaks), N+2)

Wnorder <- 4
Wnbasis <- nbreaks + Wnorder - 2
Wbreaks <- xmesh[index]
Wbasis  <- create.bspline.basis(xrng, Wnbasis, Wnorder, Wbreaks)
WfdPar  <- fdPar(fd(matrix(0,Wnbasis,1), Wbasis))

#  use smooth.morph to map sorted data into the interior of [0,1]

result  <- smooth.morph(xmesh, pmesh, c(0,1), WfdPar)
xfine   <- seq(0,1,len=101)
Wfdobj  <- result\$Wfdobj

cdffine <- result\$hfine
cdffine[1]               <- 0
cdffine[length(cdffine)] <- 1

# plot(xfine, cdffine, type="l")
# points(xmesh, pmesh)

# plot(Wfdobj)

return(list(Wfdobj=Wfdobj, cdffine=cdffine))

}

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fda documentation built on May 29, 2024, 11:26 a.m.