# Curve Registration for Exponential Family Functional Data

## Documentation for package ‘registr’ version 1.0.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

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.