fdasrvf (version 1.9.4)

optimum.reparam: Align two functions

Description

This function aligns two SRSF functions using Dynamic Programming

Usage

optimum.reparam(
  Q1,
  T1,
  Q2,
  T2,
  lambda = 0,
  method = "DP",
  w = 0.01,
  f1o = 0,
  f2o = 0
)

Arguments

Q1

srsf of function 1

T1

sample points of function 1

Q2

srsf of function 2

T2

sample points of function 2

lambda

controls amount of warping (default = 0)

method

controls which optimization method (default="DP") options are Dynamic Programming ("DP"), Coordinate Descent ("DP2"), and Riemannian BFGS ("RBFGS")

w

controls LRBFGS (default = 0.01)

f1o

initial value of f1, vector or scalar depending on q1, defaults to zero

f2o

initial value of f2, vector or scalar depending on q1, defaults to zero

Value

gam warping function

References

Srivastava, A., Wu, W., Kurtek, S., Klassen, E., Marron, J. S., May 2011. Registration of functional data using fisher-rao metric, arXiv:1103.3817v2 [math.ST].

Tucker, J. D., Wu, W., Srivastava, A., Generative Models for Function Data using Phase and Amplitude Separation, Computational Statistics and Data Analysis (2012), 10.1016/j.csda.2012.12.001.

Examples

# NOT RUN {
data("simu_data")
q = f_to_srvf(simu_data$f,simu_data$time)
gam = optimum.reparam(q[,1],simu_data$time,q[,2],simu_data$time)
# }