# Regression with Functional Data

## Documentation for package ‘refund’ version 0.1-23

- DESCRIPTION file.

## Help Pages

A B C D E F G I L M O P Q R S V X

refund-package | Regression with Functional Data

## -- A --

af | Construct an FGAM regression term
af_old | Construct an FGAM regression term

## -- B --

bayes_fosr | Bayesian Function-on-scalar regression

## -- C --

ccb.fpc | Corrected confidence bands using functional principal components
cd4 | Observed CD4 cell counts
checkError | Internal functions for the refund package
cmdscale_lanczos | Faster multi-dimensional scaling
coef.pffr | Get estimated coefficients from a pffr fit
coef.pfr | Extract coefficient functions from a fitted pfr-object
coefboot.pffr | Simple bootstrap CIs for pffr
coefficients.pfr | Extract coefficient functions from a fitted pfr-object
create.prep.func | Construct a function for preprocessing functional predictors

## -- D --

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

## -- E --

expand.call | Return call with all possible arguments

## -- F --

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 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
fpcr.setup | Internal functions for the refund package
f_sum | Sum computation 1
f_sum2 | Sum computation 2
f_sum4 | Sum computation 2
f_trace | Trace computation

## -- G --

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
gibbs_cs_fpca | Cross-sectional FoSR using a Gibbs sampler and FPCA
gibbs_cs_wish | Cross-sectional FoSR using a Gibbs sampler and Wishart prior
gibbs_mult_fpca | Multilevel FoSR using a Gibbs sampler and FPCA
gibbs_mult_wish | Multilevel FoSR using a Gibbs sampler and Wishart prior
gls_cs | Cross-sectional FoSR using GLS

## -- I --

imwd_test | Internal functions for the refund package
irreg2mat | Internal functions for the refund package

## -- L --

lf | Construct an FLM regression term
lf.vd | Construct a VDFR regression term
lf_old | Construct an FLM regression term
list2df | Internal functions for the refund package
lpeer | Longitudinal Functional Models with Structured Penalties
lpfr | Longitudinal penalized functional regression
lw.test | Internal functions for the refund package

## -- M --

mfpca.sc | Multilevel functional principal components analysis by smoothed covariance
model.matrix.pffr | Obtain model matrix for a pffr fit

## -- O --

ols_cs | Cross-sectional FoSR using GLS
Omegas | Internal functions for the refund package
osplinepen2d | Internal functions for the refund package

## -- P --

parse.predict.pfr | Internal functions for the refund package
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
postprocess.pfr | Internal functions for the refund package
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.matrix.pss.smooth | Internal functions for the refund package
predict.pffr | Prediction for penalized function-on-function regression
predict.pfr | Prediction from a fitted pfr model
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 --

Q | Simulated longitudinal data with functional predictor and scalar response, and structural information associated with predictor function
qq.pffr | QQ plots for pffr model residuals
quadWeights | Compute quadrature weights

## -- R --

re | Random effects constructor for fgam
refund | Regression with Functional Data
residuals.pffr | Obtain residuals and fitted values for a pffr models
rlrt.pfr | Likelihood Ratio Test and Restricted Likelihood Ratio Test for inference of functional predictors

## -- S --

safeDeparse | Internal functions for the refund package
sff | Construct a smooth function-on-function regression term
smooth.construct.dt.smooth.spec | Domain Transformation basis constructor
smooth.construct.fpc.smooth.spec | Basis constructor for FPC terms
smooth.construct.pco.smooth.spec | Principal coordinate ridge regression
smooth.construct.pcre.smooth.spec | mgcv-style constructor for PC-basis functional random effects
smooth.construct.peer.smooth.spec | Basis constructor for PEER terms
smooth.construct.pi.smooth.spec | Parametric Interaction basis constructor
smooth.construct.pss.smooth.spec | P-spline constructor with modified 'shrinkage' penalty
sofa | SOFA (Sequential Organ Failure Assessment) Data
summary.pffr | Summary for a pffr fit
summary.pfr | Summary for a pfr fit

## -- V --

vb_cs_fpca | Cross-sectional FoSR using Variational Bayes and FPCA
vb_cs_wish | Cross-sectional FoSR using Variational Bayes and Wishart prior
vb_mult_fpca | Multilevel FoSR using Variational Bayes and FPCA
vb_mult_wish | Multilevel FoSR using Variational Bayes and Wishart prior
vis.fgam | Visualization of FGAM objects
vis.pfr | Visualization of PFR objects

## -- X --

Xt_siginv_X | Internal computation function