Curve Registration for Exponential Family Functional Data


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Documentation for package ‘registr’ version 1.0.0

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amp_curve Simulate amplitude variance
bfpca Binary functional principal components analysis
bs_deriv Nth derivative of spline basis
constraints Define constraints for optimization of warping functions
data_clean Convert data to a 'refund' object
expectedScores Calculate expected score and score variance for the current subject.
expectedXi Estimate variational parameter for the current subject.
fpca_gauss Functional principal components analysis via variational EM
grid_subj_create Generate subject-specific grid (t_star)
h_inv_parametric One parameter parametric warping on (0, T)
lambdaF Apply lambda transformation of variational parameter.
loss_h Loss function for registration step optimization
loss_h_gradient Gradient of loss function for registration step
mean_curve Simulate mean curve
mean_sim Simulate mean
nhanes NHANES activity data
piecewise_parametric_hinv Create two-parameter piecewise (inverse) warping functions
psi1_sim Simulate PC1
psi2_sim Simulate PC2
register_fpca Register curves using constrained optimization and GFPCA
registr Register Exponential Family Functional Data
simulate_functional_data Simulate functional data
simulate_unregistered_curves Simulate unregistered curves
squareTheta Calculate quadratic form of spline basis functions for the current subject.