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refund (version 0.1-5)

Regression with Functional Data

Description

Functions for regression with functional data. The principal methods currently implemented regress (i) scalar responses on functional predictors; (ii) functional responses on scalar predictors; and (iii) functional responses on functional predictors.

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Version

Install

install.packages('refund')

Monthly Downloads

2,224

Version

0.1-5

License

GPL (>= 2)

Maintainer

Lei Huang

Last Published

October 20th, 2011

Functions in refund (0.1-5)

print.summary.pffr

Print method for summary of a pffr fit
gasoline

Octane numbers and NIR spectra of gasoline
amc

Additive model with constraints
fitted.pffr

Obtain fitted values for a pffr fit
model.matrix.pffr

Obtain model matrix for a pffr fit
predict.pffr

Prediction for penalized function-on-function regression
DTI

Diffusion Tensor Imaging: tract profiles and outcomes
fpcr

Functional principal component regression
expand.call

Return call with all possible arguments
lofocv

Leave-one-function-out cross-validation
fosr.perm

Permutation testing for function-on-scalar regression
plot.pffr

Plot a pffr fit
coef.pffr

Get estimated coefficients from a pffr
plot.fpcr

Default plotting for functional principal component regression output
refund-package

Regression with Functional Data
plot.fosr

Default plotting of function-on-scalar regression objects
pffr

Penalized function-on-function regression
fosr

Function-on-scalar regression
residuals.pffr

Obtain residuals for a pffr fit
summary.pffr

Summary for a pffr fit
refund-internal

Internal refund Functions
pfr

Penalized Functional Regression
ff

Construct a function-on-function regression term
lpfr

Longitudinal Penalized Functional Regression
pwcv

Pointwise cross-validation for function-on-scalar regression