FRegSigCom: Functional Regression using Signal Compression Approach

Signal compression methods for function-on-function regression with functional response and functional predictors, including linear models with both scalar and functional predictors for a small number of functional predictors, linear models with functional predictors for a large number of functional predictors, stepwise selection for FOF models with two-way interactions, and nonlinear models. References are linked to via the URL below.

Version: 0.2.2
Depends: fda, Matrix
Imports: Rcpp
LinkingTo: Rcpp, RcppEigen
Suggests: refund, MASS
Published: 2018-05-07
Author: Ruiyan Luo, Xin Qi
Maintainer: Ruiyan Luo <rluo at gsu.edu>
License: GPL-2
URL: https://doi.org/10.1080/01621459.2016.1164053, https://www.sciencedirect.com/science/article/pii/S0047259X16302536?via%3Dihub.
NeedsCompilation: yes
CRAN checks: FRegSigCom results

Downloads:

Reference manual: FRegSigCom.pdf
Package source: FRegSigCom_0.2.2.tar.gz
Windows binaries: r-devel: FRegSigCom_0.2.2.zip, r-release: FRegSigCom_0.2.2.zip, r-oldrel: FRegSigCom_0.2.2.zip
OS X binaries: r-release: FRegSigCom_0.2.2.tgz, r-oldrel: FRegSigCom_0.2.2.tgz
Old sources: FRegSigCom archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=FRegSigCom to link to this page.