# Regression with Functional Data

## Documentation for package ‘refund’ version 0.1-11

- DESCRIPTION file.

## Help Pages

refund-package | Regression with Functional Data
af | Construct an FGAM regression term
amc | Additive model with constraints
ccb.fpc | Corrected confidence bands using functional principal components
cd4 | Observed CD4 cell counts
checkError | Internal functions for the refund package
coef.pffr | Get estimated coefficients from a pffr fit
coefboot.pffr | Simple bootstrap CIs for pffr
decomp | Internal functions for the refund package
decomp2d | Internal functions for the refund package
decomp3d | Internal functions for the refund package
decorrelate | Internal functions for the refund package
DTI | Diffusion Tensor Imaging: tract profiles and outcomes
DTI2 | Diffusion Tensor Imaging: more fractional anisotropy profiles and outcomes
expand.call | Return call with all possible arguments
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
first.last_test | Internal functions for the refund package
fitted.pffr | Obtain fitted values for a pffr fit
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
fosr2s | Two-step function-on-scalar regression
fpca.face | Functional principal component analysis with fast covariance estimation
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
fpcr.setup | Internal functions for the refund package
gasoline | Octane numbers and NIR spectra of gasoline
getNPC.DonohoGavish | Internal functions for the refund package
getRsq | Internal functions for the refund package
getShrtlbls | Internal functions for the refund package
getSpandDist | Internal functions for the refund package
imwd_test | Internal functions for the refund package
irreg2mat | Internal functions for the refund package
lf | Construct an FLM regression term
list2df | Internal functions for the refund package
lofocv | Leave-one-function-out cross-validation
lpeer | Longitudinal Functional Models with Structured Penalties
lpfr | Longitudinal penalized functional regression
lw.test | Internal functions for the refund package
model.matrix.pffr | Obtain model matrix for a pffr fit
Omegas | Internal functions for the refund package
osplinepen2d | Internal functions for the refund package
parse.predict.pfr | Internal functions for the refund package
pcre | pffr-constructor for functional principal component-based functional random intercepts.
peer | Functional Models with Structured Penalties
PEER.Sim | Simulated longitudinal data with functional predictor and scalar response, and structural information associated with predictor function
pffr | Penalized function-on-function regression
pffrGLS | Penalized function-on-function regression with non-i.i.d. residuals
pffrSim | Simulate example data for pffr
pfr | Penalized functional regression and Longitudinal penalized functional regression
plot.fosr | Default plotting of function-on-scalar regression objects
plot.fosr.perm | Permutation testing for function-on-scalar regression
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.wcr | Default plotting for wavelet-domain scalar-on-function regression
plot.wnet | Default plotting for wavelet-domain scalar-on-function regression
postprocess.pfr | Internal functions for the refund package
predict.fgam | Prediction from a fitted FGAM model
Predict.matrix.pss.smooth | Internal functions for the refund package
predict.pffr | Prediction for penalized function-on-function regression
predict.pfr | Prediction for penalized functional regression
predict.wnet | Prediction method for generalized elastic net in the wavelet domain
preprocess.pfr | Internal functions for the refund package
print.summary.pffr | Print method for summary of a pffr fit
pspline.setting | Internal functions for the refund package
pwcv | Pointwise cross-validation for function-on-scalar regression
Q | Simulated longitudinal data with functional predictor and scalar response, and structural information associated with predictor function
reconstr | Internal functions for the refund package
reconstr2d | Internal functions for the refund package
reconstr3d | Internal functions for the refund package
refund | Regression with Functional Data
residuals.pffr | Obtain residuals for a pffr fit
rlrt.pfr | Likelihood Ratio Test and Restricted Likelihood Ratio Test for inference of functional predictors
safeDeparse | Internal functions for the refund package
sff | Construct a smooth function-on-function regression term
smooth.construct.pcre.smooth.spec | mgcv-style constructor for PC-basis functional random effects
smooth.construct.pss.smooth.spec | P-spline constructor with modified 'shrinkage' penalty
summary.pffr | Summary for a pffr fit
vis.fgam | Visualization of FGAM objects
waveletGetCV | Internal functions for the refund package
waveletGetResult | Internal functions for the refund package
waveletSetup | Internal functions for the refund package
wcr | Principal component regression and partial least squares in the wavelet domain
wcr.perm | Permutation test for wavelet-domain scalar-on-function regression
wnet | Generalized elastic net in the wavelet domain
wnet.perm | Permutation test for wavelet-domain scalar-on-function regression