Package: clr
Type: Package
Title: Curve Linear Regression via Dimension Reduction
Version: 0.1.3.9000
Authors@R: c(
    person("Amandine", "Pierrot", email = "amandine.m.pierrot@gmail.com", 
    role = c("cre", "aut")),
    person("Qiwei", "Yao", role = "ctb"),
    person("Haeran", "Cho", role = "ctb"),
    person("Yannig", "Goude", role = "ctb"),
    person("Tony", "Aldon", role = "ctb"),
    person("EDF", role = c("cph", "fnd")))
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
Depends: R (>= 2.10)
Imports: magrittr, lubridate, dplyr, stats
Config/roxygen2/version: 8.1.0
Repository: https://apierrot.r-universe.dev
Date/Publication: 2026-08-31 22:27:57 UTC
RemoteUrl: https://github.com/apierrot/clr
RemoteRef: HEAD
RemoteSha: 296eb48a78888d693244377ee1246bfff508f5d0
NeedsCompilation: no
Packaged: 2026-10-01 07:36:25 UTC; root
Author: Amandine Pierrot [cre, aut],
  Qiwei Yao [ctb],
  Haeran Cho [ctb],
  Yannig Goude [ctb],
  Tony Aldon [ctb],
  EDF [cph, fnd]