refund: 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.

Version: 0.1-17
Depends: R (≥ 2.14.0)
Imports: fda, Matrix, lattice, boot, mgcv (≥ 1.8-12), MASS, magic, nlme, gamm4, lme4, RLRsim, splines, grpreg, ggplot2, stats, pbs, methods
Suggests: RColorBrewer, reshape2, dtw
Published: 2018-05-15
Author: Jeff Goldsmith [aut], Fabian Scheipl [aut], Lei Huang [aut], Julia Wrobel [aut, cre], Jonathan Gellar [aut], Jaroslaw Harezlak [aut], Mathew W. McLean [aut], Bruce Swihart [aut], Luo Xiao [aut], Ciprian Crainiceanu [aut], Philip T. Reiss [aut], Yakuan Chen [ctb], Sonja Greven [ctb], Lan Huo [ctb], Madan Gopal Kundu [ctb], So Young Park [ctb], David L. Miller [ctb], Ana-Maria Staicu [ctb]
Maintainer: Julia Wrobel <jw3134 at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
In views: FunctionalData
CRAN checks: refund results


Reference manual: refund.pdf
Package source: refund_0.1-17.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: refund_0.1-17.tgz, r-oldrel: refund_0.1-17.tgz
Old sources: refund archive

Reverse dependencies:

Reverse depends: sparseFLMM
Reverse imports: refund.shiny, reinforcedPred
Reverse suggests: FDboost, FRegSigCom, mlr


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