fit_mean: Mean estimation for open planar curves.

In elastes: Elastic Full Procrustes Means for Sparse and Irregular Planar Curves

Mean estimation for open planar curves.

Description

Fits an elastic full Procrustes mean for open, planar curves. Is usually called from compute_elastic_shape_mean.

Usage

fit_mean(
  srv_data_curves,
  knots,
  penalty,
  var_type,
  pfit_method,
  max_iter,
  type,
  eps,
  cluster,
  verbose,
  smooth_warp
)

Arguments

srv_data_curves	list of data.frames with srv vectors in each row.curves
knots	set of knots for the mean spline curve
penalty	the penalty to use in the covariance smoothing step. use '-1' for no penalty.
var_type	(experimental) assume "smooth", "constant" or "zero" measurement-error variance along t
pfit_method	(experimental) "smooth" or "polygon"
max_iter	maximal number of iterations
type	if "smooth" linear srv-splines are used which results in a differentiable mean curve if "polygon" the mean will be piecewise linear.
eps	the algorithm stops if L2 norm of coefficients changes less
cluster	a cluster object for use in the bam call
verbose	print iterations
smooth_warp	(experimental) controls the weighting of original and smoothed observations over the iterations, if pfit_method == "smooth".

Value

a list with entries

type	"smooth" or "polygon"
coefs	coefs srv spline coefficients of the estimated mean
knots	spline knots
penalty	penalty used in the covariance estimation
distances	distances to mean
fit	a list containing t_optimsoptimal parametrizations G_optimsoptimal rotations b_optimsoptimal scalings n_optimsoptimal re-normalization n_iternumber of iterations until convergence gram the mean basis Gram matrix, cov_fit the covariance smoothing objects in the final iteration, cov_pca cov coef matrix pca object in the final iteration and pfit_coefs the mean basis coefs of smoothed pfits in the final iteration

elastes documentation built on Aug. 21, 2023, 5:12 p.m.