Package: clr
Type: Package
Title: Curve Linear Regression via Dimension Reduction
Version: 0.1.2
Author: Amandine Pierrot 
    with contributions and/or help from Qiwei Yao, Haeran Cho, Yannig Goude and 
    Tony Aldon.
Maintainer: Amandine Pierrot <amandine.m.pierrot@gmail.com>
Copyright: EDF R&D 2017
Description: 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. 
License: LGPL (>= 2.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 2.10)
Imports: magrittr, lubridate, dplyr, stats
NeedsCompilation: no
Packaged: 2019-07-10 10:42:17 UTC; amandinepierrot
Repository: CRAN
Date/Publication: 2019-07-29 09:00:02 UTC
Built: R 4.1.0; ; 2020-08-03 06:02:05 UTC; windows
