| 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. |