refund v0.1-23

0

Monthly downloads

0th

Percentile

Regression with Functional Data

Methods for regression for functional data, including function-on-scalar, scalar-on-function, and function-on-function regression. Some of the functions are applicable to image data.

Functions in refund

Name Description
DTI Diffusion Tensor Imaging: tract profiles and outcomes
Predict.matrix.pcre.random.effect mgcv-style constructor for prediction of PC-basis functional random effects
Predict.matrix.fpc.smooth mgcv-style constructor for prediction of FPC terms
af Construct an FGAM regression term
DTI2 Diffusion Tensor Imaging: more fractional anisotropy profiles and outcomes
Xt_siginv_X Internal computation function
Predict.matrix.pi.smooth Predict.matrix method for pi basis
Predict.matrix.peer.smooth mgcv-style constructor for prediction of PEER terms
PEER.Sim Simulated longitudinal data with functional predictor and scalar response, and structural information associated with predictor function
Predict.matrix.dt.smooth Predict.matrix method for dt basis
coef.pffr Get estimated coefficients from a pffr fit
cmdscale_lanczos Faster multi-dimensional scaling
cd4 Observed CD4 cell counts
af_old Construct an FGAM regression term
amc Additive model with constraints
expand.call Return call with all possible arguments
f_sum Sum computation 1
fbps Sandwich smoother for matrix data
f_trace Trace computation
bayes_fosr Bayesian Function-on-scalar regression
ffpcplot Plot PC-based function-on-function regression terms
ccb.fpc Corrected confidence bands using functional principal components
fgam Functional Generalized Additive Models
fosr2s Two-step function-on-scalar regression
create.prep.func Construct a function for preprocessing functional predictors
coefficients.pfr Extract coefficient functions from a fitted pfr-object
fosr.vs Function-on Scalar Regression with variable selection
fpca.lfda Longitudinal Functional Data Analysis using FPCA
fpca.sc Functional principal components analysis by smoothed covariance
coefboot.pffr Simple bootstrap CIs for pffr
ffpc Construct a PC-based function-on-function regression term
ff Construct a function-on-function regression term
f_sum2 Sum computation 2
fosr.perm Permutation testing for function-on-scalar regression
fosr Function-on-scalar regression
lf Construct an FLM regression term
lf.vd Construct a VDFR regression term
fpca2s Functional principal component analysis by a two-stage method
gibbs_mult_fpca Multilevel FoSR using a Gibbs sampler and FPCA
gibbs_cs_wish Cross-sectional FoSR using a Gibbs sampler and Wishart prior
fpca.ssvd Smoothed FPCA via iterative penalized rank one SVDs.
getTF Get recognized transformation function
gibbs_cs_fpca Cross-sectional FoSR using a Gibbs sampler and FPCA
fpca.face Functional principal component analysis with fast covariance estimation
fpc Construct a FPC regression term
pcre pffr-constructor for functional principal component-based functional random intercepts.
peer Construct a PEER regression term in a pfr formula
lpeer Longitudinal Functional Models with Structured Penalties
gasoline Octane numbers and NIR spectra of gasoline
fpcr Functional principal component regression
mfpca.sc Multilevel functional principal components analysis by smoothed covariance
lf_old Construct an FLM regression term
pffr.check Some diagnostics for a fitted pffr model
plot.pfr Plot a pfr object
model.matrix.pffr Obtain model matrix for a pffr fit
predict.fbps Prediction for fast bivariate P-spline (fbps)
pffrGLS Penalized function-on-function regression with non-i.i.d. residuals
ols_cs Cross-sectional FoSR using GLS
pco_predict_preprocess Make predictions using pco basis terms
plot.fosr.vs Plot for Function-on Scalar Regression with variable selection
plot.fosr Default plotting of function-on-scalar regression objects
plot.fpcr Default plotting for functional principal component regression output
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
smooth.construct.fpc.smooth.spec Basis constructor for FPC terms
smooth.construct.pco.smooth.spec Principal coordinate ridge regression
f_sum4 Sum computation 2
lpfr Longitudinal penalized functional regression
qq.pffr QQ plots for pffr model residuals
smooth.construct.pcre.smooth.spec mgcv-style constructor for PC-basis functional random effects
pwcv Pointwise cross-validation for function-on-scalar regression
vb_mult_wish Multilevel FoSR using Variational Bayes and Wishart prior
plot.lpeer Plotting of estimated regression functions obtained through lpeer()
vis.pfr Visualization of PFR objects
smooth.construct.peer.smooth.spec Basis constructor for PEER terms
pfr_plot.gam Local version of plot.gam
predict.fosr.vs Prediction for Function-on Scalar Regression with variable selection
pfr_old Penalized Functional Regression (old version)
vis.fgam Visualization of FGAM objects
sff Construct a smooth function-on-function regression term
quadWeights Compute quadrature weights
summary.pfr Summary for a pfr fit
smooth.construct.dt.smooth.spec Domain Transformation basis constructor
predict.pffr Prediction for penalized function-on-function regression
re Random effects constructor for fgam
lofocv Leave-one-function-out cross-validation
gls_cs Cross-sectional FoSR using GLS
gibbs_mult_wish Multilevel FoSR using a Gibbs sampler and Wishart prior
vb_cs_fpca Cross-sectional FoSR using Variational Bayes and FPCA
peer_old Functional Models with Structured Penalties
pfr Penalized Functional Regression
plot.pffr Plot a pffr fit
pffrSim Simulate example data for pffr
refund-internal Internal functions for the refund package
plot.peer Plotting of estimated regression functions obtained through peer()
refund-package Regression with Functional Data
pffr Penalized flexible functional regression
predict.fgam Prediction from a fitted FGAM model
predict.pfr Prediction from a fitted pfr model
predict.fosr Prediction from a fitted bayes_fosr model
sofa SOFA (Sequential Organ Failure Assessment) Data
vb_cs_wish Cross-sectional FoSR using Variational Bayes and Wishart prior
summary.pffr Summary for a pffr fit
vb_mult_fpca Multilevel FoSR using Variational Bayes and FPCA
smooth.construct.pi.smooth.spec Parametric Interaction basis constructor
print.summary.pffr Print method for summary of a pffr fit
smooth.construct.pss.smooth.spec P-spline constructor with modified 'shrinkage' penalty
No Results!

Last month downloads

Details

Type Package
Date 2020-12-03
License GPL (>= 2)
LazyLoad yes
LazyData true
Repository CRAN
Collate 'Omegas.R' 'af.R' 'af_old.R' 'amc.R' 'ccb.fpc.R' 'create.prep.func.R' 'coefficients.pfr.R' 'dt_basis.R' 'irreg2mat.R' 'fbps.R' 'fgam.R' 'fosr.R' 'fosr.perm.R' 'fosr.perm.fit.R' 'fosr.perm.test.R' 'fosr.vs.R' 'fosr2s.R' 'fpc.R' 'fpca2s.R' 'fpca.sc.R' 'fpca.face.R' 'fpca.ssvd.R' 'fpcr.R' 'fpcr.setup.R' 'lf.R' 'lf_old.R' 'lf.vd.R' 'lofocv.R' 'lpeer.R' 'lpfr.R' 'quadWeights.R' 'lw.test.R' 'osplinepen2d.R' 'parse.predict.pfr.R' 'peer.R' 'peer_old.R' 'pffr-ff.R' 'pffr-ffpc.R' 'pffr-methods.R' 'pffr-pcre.R' 'pffr-robust.R' 'pffr-sff.R' 'pffr-utilities.R' 'pffr.R' 'pfr.R' 'pfr_old.R' 'pi_basis.R' 'plot.fosr.R' 'plot.fosr.perm.R' 'plot.fosr.vs.R' 'plot.fpcr.R' 'plot.lpeer.R' 'plot.peer.R' 'plot.pfr.R' 'poridge.R' 'postprocess.pfr.R' 'predict.fgam.R' 'predict.fosr.R' 'predict.pfr.R' 'predict.pfr_old.R' 'preprocess.pfr.R' 'pspline.setting.R' 'pwcv.R' 'summary.pfr.R' 're.R' 'rlrt.pfr.R' 'vis.fgam.R' 'predict.fosr.vs.R' 'CD4-data.R' 'DTI-data.R' 'DTI2-data.R' 'PEER.Sim-data.R' 'gasoline-data.R' 'vis.pfr.R' 'GLS_CS.R' 'Gibbs_CS_FPCA.R' 'Gibbs_CS_Wish.R' 'Gibbs_Mult_FPCA.R' 'Gibbs_Mult_Wish.R' 'OLS_CS.R' 'VB_CS_FPCA.R' 'VB_CS_Wish.R' 'VB_Mult_FPCA.R' 'VB_Mult_Wish.R' 'XtSiginvX.R' 'bayes_fosr.R' 'f_sum.R' 'f_sum2.R' 'f_sum4.R' 'f_trace.R' 'mfpca.sc.R' 'fpca.lfda.R' 'predict.fbps.R' 'select_knots.R'
RoxygenNote 7.1.1
NeedsCompilation no
Packaged 2020-12-04 14:36:34 UTC; juliawrobel
Date/Publication 2020-12-04 16:00:03 UTC

Include our badge in your README

[![Rdoc](http://www.rdocumentation.org/badges/version/refund)](http://www.rdocumentation.org/packages/refund)