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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: | 0.1-37 |
Depends: | R (≥ 3.5.0) |
Imports: | fda, Matrix, lattice, boot, mgcv (≥ 1.9), MASS, magic, nlme, gamm4, lme4, RLRsim, splines, grpreg, ggplot2, stats, pbs, methods |
Suggests: | RColorBrewer, reshape2, testthat |
Published: | 2024-09-20 |
DOI: | 10.32614/CRAN.package.refund |
Author: | Jeff Goldsmith [aut], Fabian Scheipl [aut], Lei Huang [aut], Julia Wrobel [aut, cre], Chongzhi Di [aut], 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], Erjia Cui [aut], Ruonan Li [ctb], Zheyuan Li [ctb] |
Maintainer: | Julia Wrobel <julia.wrobel at emory.edu> |
BugReports: | https://github.com/refunders/refund/issues |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: | https://github.com/refunders/refund |
NeedsCompilation: | no |
In views: | FunctionalData |
CRAN checks: | refund results |
Reference manual: | refund.pdf |
Package source: | refund_0.1-37.tar.gz |
Windows binaries: | r-devel: refund_0.1-37.zip, r-release: refund_0.1-37.zip, r-oldrel: refund_0.1-37.zip |
macOS binaries: | r-release (arm64): refund_0.1-37.tgz, r-oldrel (arm64): refund_0.1-37.tgz, r-release (x86_64): refund_0.1-37.tgz, r-oldrel (x86_64): refund_0.1-37.tgz |
Old sources: | refund archive |
Reverse depends: | funmediation, sparseFLMM |
Reverse imports: | fastFMM, longsurr, MJMbamlss, mMARCH.AC, mxfda, postGGIR, refund.shiny, rmfanova |
Reverse suggests: | FDboost, fPASS, ghcm, gmfamm, mlr, runDRT, spfda, tf |
Please use the canonical form https://CRAN.R-project.org/package=refund to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.