amp_curve               Simulate amplitude variance
bfpca                   Binary functional principal components analysis
bfpca_argPreparation    Internal main preparation function for bfpca
bfpca_optimization      Internal main optimization for bfpca
bs_deriv                Nth derivative of spline basis
coarsen_index           Coarsen an index vector to a given resolution
constraints             Define constraints for optimization of warping
                        functions
cov_hall                Covariance estimation after Hall et al. (2008)
crossprods_irregular    Crossproduct computation for highly irregular
                        grids
crossprods_regular      Crossproduct computation for mostly regular
                        grids
data_clean              Convert data to a 'refund' object
deriv.inv.logit         Estimate the derivative of the logit function
determine_npc           Determine the number of FPCs based on the share
                        of explained variance
ensure_proper_beta      Correct slightly improper parameter vectors
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
fpca_gauss_argPreparation
                        Internal main preparation function for
                        fpca_gauss
fpca_gauss_optimization
                        Internal main optimization for fpca_gauss
gfpca_twoStep           Generalized functional principal component
                        analysis
grid_subj_create        Generate subject-specific grid (t_star)
growth_incomplete       Berkeley Growth Study data with simulated
                        incompleteness
initial_params          Create initial parameters for (inverse) warping
                        functions
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_linear2_hinv
                        Create two-parameter piecewise linear (inverse)
                        warping functions
plot.fpca               Plot the results of a functional PCA
psi1_sim                Simulate PC1
psi2_sim                Simulate PC2
register_fpca           Register curves using constrained optimization
                        and GFPCA
registr                 Register (in)complete curves from exponential
                        family
registr_oneCurve        Internal function to register one curve
simulate_functional_data
                        Simulate functional data
simulate_unregistered_curves
                        Simulate unregistered curves
squareTheta             Calculate quadratic form of spline basis
                        functions for the current subject.
