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refund (version 0.1-4)

Regression with Functional Data

Description

Functions for regression with functional data. The principal methods currently implemented are (I) regression of scalar responses on functional predictors, by (longitudinal) penalized functional regression and functional principal component regression; and (II) regression of functional responses on scalar predictors, by penalized OLS or GLS.

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Version

Install

install.packages('refund')

Monthly Downloads

2,224

Version

0.1-4

License

GPL (>= 2)

Maintainer

Lei Huang

Last Published

July 23rd, 2011

Functions in refund (0.1-4)

pwcv

Pointwise cross-validation for function-on-scalar regression
gasoline

Octane numbers and NIR spectra of gasoline
fpcr

Functional principal component regression
refund-package

Regression with Functional Data
amc

Additive model with constraints
plot.fpcr

Default plotting for functional principal component regression output
lpfr

Longitudinal Penalized Functional Regression
DTI

Diffusion Tensor Imaging: tract profiles and outcomes
lofocv

Leave-one-function-out cross-validation
pfr

Penalized Functional Regression
plot.fosr

Default plotting of function-on-scalar regression objects
fosr

Function-on-scalar regression
fosr.perm

Permutation testing for function-on-scalar regression