FRegSigCom: Functional Regression using Signal Compression Approach

Signal compression methods for function-on-function (FOF) 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, and nonlinear models. Ruiyan Luo and Xin Qi (2017) <doi:10.1080/01621459.2016.1164053>.

Version: 0.1.0
Imports: fda
Suggests: refund, MASS
Published: 2017-09-06
Author: Ruiyan Luo, Xin Qi
Maintainer: Ruiyan Luo <rluo at gsu.edu>
License: GPL-2
NeedsCompilation: no
CRAN checks: FRegSigCom results

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Reference manual: FRegSigCom.pdf
Package source: FRegSigCom_0.1.0.tar.gz
Windows binaries: r-devel: FRegSigCom_0.1.0.zip, r-release: FRegSigCom_0.1.0.zip, r-oldrel: FRegSigCom_0.1.0.zip
OS X El Capitan binaries: r-release: FRegSigCom_0.1.0.tgz
OS X Mavericks binaries: r-oldrel: FRegSigCom_0.1.0.tgz

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