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 |