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fda (version 1.2.2)

register.fd: Register Functional Data Objects Using a Continuous Criterion

Description

Curves are aligned with a target or template curve using a continuous criterion. By aligned is meant that the shape of each curve is matched as closely as possible to that of the target by means of a smooth increasing transformation of the argument, or a warping function.

Usage

register.fd(y0fd, yfd, WfdParobj, conv=1e-04,
            iterlim=20, dbglev=1, periodic=FALSE, crit=2)

Arguments

y0fd
a functional data object defining the target for registration. It must be univariate and it must define a single functional observation.
yfd
a functional data object defining the functions to be registered to target yfd0.
WfdParobj
a functional parameter object for a single function. This function is used as the initial value in the estimation of a function $W(t)$ that defines the warping function $h(t)$ that registers a particular curve. The object also contains information on a r
conv
a criterion for convergence of the iterations.
iterlim
a limit on the number of iterations.
dbglev
either 0, 1, or 2. This controls the amount information printed out on each iteration, with 0 implying no output, 1 intermediate output level, and 2 full output. If output is desired, it is helpful to turn off the output buffering option of S-PLUS.
periodic
a logical variable: if TRUE, the functions are considered to be periodic, in which case a constant can be added to all argument values after they are warped.
crit
an integer that is either 1 or 2 that indicates the nature of the continuous registration criterion that is used. If 1, the criterion is least squares, and if 2, the criterion is the minimum eigenvalue of a cross-product matrix. In general, criterion 2

Value

  • a named list of length 3 containing the following components:
  • regfdA functional data object containing the registered functions.
  • WfdA functional data object containing the functions $h W(t)$ that define the warping functions $h(t)$.
  • shiftIf the functions are periodic, this is a vector of time shifts.

Details

The warping function that smoothly and monotonely transforms the argument is defined by Wfd is the same as that defines the monotone smoothing function in for function smooth.monotone. See the help file for that function for further details.

See Also

smooth.monotone, smooth.morph

Examples

Run this code
#See the analyses of the growth data for examples.

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