time_warping | R Documentation |
This function aligns a collection of 1
-dimensional curves that are
observed on the same grid.
time_warping(
f,
time,
lambda = 0,
penalty_method = c("roughness", "geodesic", "norm"),
centroid_type = c("mean", "median"),
center_warpings = TRUE,
smooth_data = FALSE,
sparam = 25L,
parallel = FALSE,
optim_method = c("DP", "DPo", "DP2", "RBFGS"),
max_iter = 20L
)
f |
A numeric matrix of shape |
time |
A numeric vector of length |
lambda |
A numeric value specifying the elasticity. Defaults to |
penalty_method |
A string specifying the penalty term used in the
formulation of the cost function to minimize for alignment. Choices are
|
centroid_type |
A string specifying the type of centroid to align to.
Choices are |
center_warpings |
A boolean specifying whether to center the estimated
warping functions. Defaults to |
smooth_data |
A boolean specifying whether to smooth curves using a box
filter. Defaults to |
sparam |
An integer value specifying the number of times to apply the
box filter. Defaults to |
parallel |
A boolean specifying whether to run calculations in parallel.
Defaults to |
optim_method |
A string specifying the algorithm used for optimization.
Choices are |
max_iter |
An integer value specifying the maximum number of iterations.
Defaults to |
An object of class fdawarp
which is a list with the following
components:
time
: a numeric vector of length M
storing the original grid;
f0
: a numeric matrix of shape M \times N
storing the original
sample of N
functions observed on a grid of size M
;
q0
: a numeric matrix of the same shape as f0
storing the original
SRSFs;
fn
: a numeric matrix of the same shape as f0
storing the aligned
functions;
qn
: a numeric matrix of the same shape as f0
storing the aligned SRSFs;
fmean
: a numeric vector of length M
storing the mean or median
curve;
mqn
: a numeric vector of length M
storing the mean or median SRSF;
warping_functions
: a numeric matrix of the same shape as f0
storing the
estimated warping functions;
original_variance
: a numeric value storing the variance of the original
sample;
amplitude_variance
: a numeric value storing the variance in amplitude of
the aligned sample;
phase_variance
: a numeric value storing the variance in phase of the
aligned sample;
qun
: a numeric vector of maximum length max_iter + 2
storing the values
of the cost function after each iteration;
lambda
: the input parameter lambda
which specifies the elasticity;
centroid_type
: the input centroid type;
optim_method
: the input optimization method;
inverse_average_warping_function
: the inverse of the mean estimated
warping function;
rsamps
: TO DO.
Srivastava, A., Wu, W., Kurtek, S., Klassen, E., Marron, J. S., May 2011. Registration of functional data using Fisher-Rao metric, arXiv:1103.3817v2.
Tucker, J. D., Wu, W., Srivastava, A., Generative models for functional data using phase and amplitude Separation, Computational Statistics and Data Analysis (2012), 10.1016/j.csda.2012.12.001.
## Not run:
out <- time_warping(simu_data$f, simu_data$time)
## End(Not run)
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