fbps |
Sandwich smoother for matrix data |
ff |
Construct a function-on-function regression term |
ffpc |
Construct a PC-based function-on-function regression term |
ffpcplot |
Plot PC-based function-on-function regression terms |
fgam |
Functional Generalized Additive Models |
fitted.pffr |
Obtain residuals and fitted values for a pffr models |
fosr |
Function-on-scalar regression |
fosr.perm |
Permutation testing for function-on-scalar regression |
fosr.perm.fit |
Permutation testing for function-on-scalar regression |
fosr.perm.test |
Permutation testing for function-on-scalar regression |
fosr.vs |
Function-on Scalar Regression with variable selection |
fosr2s |
Two-step function-on-scalar regression |
fpc |
Construct a FPC regression term |
fpca.face |
Functional principal component analysis with fast covariance estimation |
fpca.lfda |
Longitudinal Functional Data Analysis using FPCA |
fpca.sc |
Functional principal components analysis by smoothed covariance |
fpca.ssvd |
Smoothed FPCA via iterative penalized rank one SVDs. |
fpca2s |
Functional principal component analysis by a two-stage method |
fpcr |
Functional principal component regression |
f_sum |
Sum computation 1 |
f_sum2 |
Sum computation 2 |
f_sum4 |
Sum computation 2 |
f_trace |
Trace computation |
pco |
Principal coordinate ridge regression |
pco_predict_preprocess |
Make predictions using pco basis terms |
pcre |
pffr-constructor for functional principal component-based functional random intercepts. |
peer |
Construct a PEER regression term in a 'pfr' formula |
PEER.Sim |
Simulated longitudinal data with functional predictor and scalar response, and structural information associated with predictor function |
peer_old |
Functional Models with Structured Penalties |
pffr |
Penalized flexible functional regression |
pffr.check |
Some diagnostics for a fitted pffr model |
pffrGLS |
Penalized function-on-function regression with non-i.i.d. residuals |
pffrSim |
Simulate example data for pffr |
pfr |
Penalized Functional Regression |
pfr_old |
Penalized Functional Regression (old version) |
plot.fosr |
Default plotting of function-on-scalar regression objects |
plot.fosr.perm |
Permutation testing for function-on-scalar regression |
plot.fosr.vs |
Plot for Function-on Scalar Regression with variable selection |
plot.fpcr |
Default plotting for functional principal component regression output |
plot.lpeer |
Plotting of estimated regression functions obtained through 'lpeer()' |
plot.peer |
Plotting of estimated regression functions obtained through 'peer()' |
plot.pffr |
Plot a pffr fit |
plot.pfr |
Plot a pfr object |
poridge |
Principal coordinate ridge regression |
predict.fbps |
Prediction for fast bivariate _P_-spline (fbps) |
predict.fgam |
Prediction from a fitted FGAM model |
predict.fosr |
Prediction from a fitted bayes_fosr model |
predict.fosr.vs |
Prediction for Function-on Scalar Regression with variable selection |
Predict.matrix.dt.smooth |
Predict.matrix method for dt basis |
Predict.matrix.fpc.smooth |
mgcv-style constructor for prediction of FPC terms |
Predict.matrix.pco.smooth |
Principal coordinate ridge regression |
Predict.matrix.pcre.random.effect |
mgcv-style constructor for prediction of PC-basis functional random effects |
Predict.matrix.peer.smooth |
mgcv-style constructor for prediction of PEER terms |
Predict.matrix.pi.smooth |
Predict.matrix method for pi basis |
predict.pffr |
Prediction for penalized function-on-function regression |
predict.pfr |
Prediction from a fitted pfr model |
print.summary.pffr |
Print method for summary of a pffr fit |
pwcv |
Pointwise cross-validation for function-on-scalar regression |