Curve Linear Regression via Dimension Reduction R package clr version 0.1.2 A new methodology for linear regression with both curve response and curve regressors, which is described in Cho, Goude, Brossat and Yao (2013) <doi:10.1080/01621459.2012.722900> and (2015) <doi:10.1007/978-3-319-18732-7_3>. The key idea behind this methodology is dimension reduction based on a singular value decomposition in a Hilbert space, which reduces the curve regression problem to several scalar linear regression problems. Software Depends: R (>= 2.10) Imports: magrittr, lubridate, dplyr, stats Amandine Pierrot <amandine.m.pierrot@gmail.com> Comprehensive R Archive Network (CRAN) Amandine Pierrot with contributions and/or help from Qiwei Yao, Haeran Cho, Yannig Goude and Tony Aldon. LGPL (>= 2.0) 2019-07-29 application/tgz https://CRAN.R-project.org/package=clr doi:10.32614/CRAN.package.clr