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.
