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Implementation of commonly used penalized functional linear regression models, including the Smooth and Locally Sparse (SLoS) method by Lin et al. (2016) <doi:10.1080/10618600.2016.1195273>, Nested Group bridge Regression (NGR) method by Guan et al. (2020) <doi:10.1080/10618600.2020.1713797>, Functional Linear Regression That's interpretable (FLIRTI) by James et al. (2009) <doi:10.1214/08-AOS641>, and the Penalized B-spline regression method.
Version: | 1.1.0 |
Depends: | R (≥ 3.5.0) |
Imports: | fda, MASS, flare, psych, glmnet, stats, utils |
Published: | 2024-08-22 |
DOI: | 10.32614/CRAN.package.PFLR |
Author: | Tianyu Guan [aut], Haolun Shi [aut, cre, cph], Rob Cameron [aut], Zhenhua Lin [aut] |
Maintainer: | Haolun Shi <shl2003 at connect.hku.hk> |
License: | GPL-2 |
NeedsCompilation: | no |
CRAN checks: | PFLR results |
Reference manual: | PFLR.pdf |
Package source: | PFLR_1.1.0.tar.gz |
Windows binaries: | r-devel: PFLR_1.1.0.zip, r-release: PFLR_1.1.0.zip, r-oldrel: PFLR_1.1.0.zip |
macOS binaries: | r-release (arm64): PFLR_1.1.0.tgz, r-oldrel (arm64): PFLR_1.1.0.tgz, r-release (x86_64): PFLR_1.1.0.tgz, r-oldrel (x86_64): PFLR_1.1.0.tgz |
Old sources: | PFLR archive |
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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.