Signal compression methods for functional regression. It includes various function-on-function (FOF) regression models such as the linear FOF model with functional response and both scalar and functional predictors for a small number of functional predictors, linear FOF models with a large number of functional predictors, linear FOF model for spiky data, stepwise selection for FOF models with two-way interactions, and nonlinear FOF models. It also includes scalar-on-function regression models with single (SOF) or multivariate (mSOF) scalar response variable, and SOF model for spiky data.
| Version: | 0.3.0 |
| Depends: | R (≥ 2.10), fda, Matrix |
| Imports: | Rcpp |
| LinkingTo: | Rcpp, RcppEigen |
| Suggests: | refund, MASS, wavethresh |
| Published: | 2018-11-15 |
| Author: | Ruiyan Luo, Xin Qi |
| Maintainer: | Ruiyan Luo <rluo at gsu.edu> |
| License: | GPL-2 |
| URL: | http://sites.gsu.edu/rluo/, http://sites.gsu.edu/xqi3/ |
| NeedsCompilation: | yes |
| CRAN checks: | FRegSigCom results |
| Reference manual: | FRegSigCom.pdf |
| Package source: | FRegSigCom_0.3.0.tar.gz |
| Windows binaries: | r-devel: FRegSigCom_0.3.0.zip, r-release: FRegSigCom_0.3.0.zip, r-oldrel: FRegSigCom_0.3.0.zip |
| OS X binaries: | r-release: FRegSigCom_0.3.0.tgz, r-oldrel: FRegSigCom_0.3.0.tgz |
| Old sources: | FRegSigCom archive |
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