fda (version 2.1.1)

plot.pda.fd: Plot Principle Differential Analysis Components

Description

Plots the results of pda.fd, allows the user to group coefficient functions by variable, equation, derivative or combination of them.

Usage

## S3 method for class 'pda.fd':
plot(x,whichdim=1,npts=501,...)

Arguments

x

an object of class pda.fd.

whichdim

which dimension to use as grouping variables 1{ coefficients of each variable differential equation} 2{ coefficient functions for each equation} 3{ coefficients of derivatives of each variable}

npts

number of points to use for plotting.

...

other arguments for 'plot'.

Value

• invisible(NULL)

Details

Produces one plot for each coefficient function in a principle differential analysis.

See Also

pda.fd eigen.pda

Examples

#  A pda analysis of the handwriting data

fdaarray = handwrit
fdatime  <- seq(0, 2.3, len=1401)

#  basis for coordinates

fdarange <- c(0, 2.3)
breaks = seq(0,2.3,length.out=501)
norder = 6
fdabasis = create.bspline.basis(fdarange,norder=norder,breaks=breaks)

#  parameter object for coordinates

fdaPar = fdPar(fdabasis,int2Lfd(4),1e-8)

#  coordinate functions and a list tontaining them

Xfd = smooth.basis(fdatime, fdaarray[,,1], fdaPar)$fd
Yfd = smooth.basis(fdatime, fdaarray[,,2], fdaPar)$fd

xfdlist = list(Xfd, Yfd)

#  basis and parameter object for weight functions

fdabasis2 = create.bspline.basis(fdarange,norder=norder,nbasis=51)
pdaPar = fdPar(fdabasis2,1,1e-8)

pdaParlist = list(pdaPar, pdaPar)

bwtlist = list( list(pdaParlist,pdaParlist), list(pdaParlist,pdaParlist) )

#  do the second order pda

pdaList = pda.fd(xfdlist, bwtlist)

# plot the results

plot(pdaList,whichdim=1)
plot(pdaList,whichdim=2)
plot(pdaList,whichdim=3)

plot(pdaList,whichdim=c(1,2))
plot(pdaList,whichdim=c(1,3))
plot(pdaList,whichdim=c(2,3))

plot(pdaList,whichdim=1:3)