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elasdics (version 1.1.3)

Elastic Analysis of Sparse, Dense and Irregular Curves

Description

Provides functions to align curves and to compute mean curves based on the elastic distance defined in the square-root-velocity framework. For more details on this framework see Srivastava and Klassen (2016, ). For more theoretical details on our methods and algorithms see Steyer et al. (2023, ) and Steyer et al. (2023, ).

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Version

Install

install.packages('elasdics')

Monthly Downloads

246

Version

1.1.3

License

GPL-3

Maintainer

Lisa Steyer

Last Published

January 25th, 2024

Functions in elasdics (1.1.3)

get_evals

Evaluate a curve on a grid
get_srv_from_points

Helper functions for curve data measured at discrete points
project_curve_on_closed

Close open curve via projection on derivative level.
srvf_to_curve

Re-transform srv curve back to curve
elasdics

elasdics: elastic analysis of sparse, dense and irregular curves.
compute_elastic_mean

Compute a elastic mean for a collection of curves
find_optimal_t_discrete_closed

Finds optimal alignment for discrete closed curves
find_optimal_t

Optimal alignment to a smooth curve
fit_elastic_regression

Compute a elastic mean for a collection of curves
plot.elastic_reg_model

Plot method for planar elastic regression models
fit_mean

Fitting function for open curves
fit_mean_closed

Fitting function for open curves
find_optimal_t_discrete

Finds optimal alignment for discrete open curves
align_curves

Align two curves measured at discrete points
center_curve

Centers curves for plotting
plot.aligned_curves

Plot method for aligned curves
optimise_one_coord_analytic

Does optimization in one parameter direction
plot.elastic_mean

Plot method for planar elastic mean curves
predict.elastic_reg_model

Predict method for elastic regression models
optimise_one_coord_analytic_closed

Does optimization in one parameter direction