This function aligns a collection of functions using the elastic square-root slope (srsf) framework.
time_warping(
f,
time,
lambda = 0,
method = "mean",
showplot = TRUE,
smooth_data = FALSE,
sparam = 25,
parallel = FALSE,
omethod = "DP",
MaxItr = 20
)
matrix (\(N\) x \(M\)) of \(M\) functions with \(N\) samples
vector of size \(N\) describing the sample points
controls the elasticity (default = 0)
warp and calculate to Karcher Mean or Median (options = "mean" or "median", default = "mean")
shows plots of functions (default = T)
smooth data using box filter (default = F)
number of times to apply box filter (default = 25)
enable parallel mode using foreach
and
doParallel
package (default=F)
optimization method (DP,DP2,RBFGS)
maximum number of iterations
Returns a fdawarp object containing
original functions
aligned functions - matrix (\(N\) x \(M\)) of \(M\) functions with \(N\) samples
aligned SRSFs - similar structure to fn
original SRSF - similar structure to fn
function mean or median - vector of length \(N\)
SRSF mean or median - vector of length \(N\)
warping functions - similar structure to fn
Original Variance of Functions
Amplitude Variance
Phase Variance
Cost Function Value
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.
# NOT RUN {
data("simu_data")
out = time_warping(simu_data$f,simu_data$time)
# }
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