clr (0.1.2)

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Curve Linear Regression via Dimension Reduction.

A new methodology for linear regression with both curve response and curve regressors, which is described in Cho, Goude, Brossat and Yao (2013) and (2015) . 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.

Maintainer: Amandine Pierrot
Author(s): Amandine Pierrot with contributions and/or help from Qiwei Yao, Haeran Cho, Yannig Goude and Tony Aldon.

License: LGPL (>= 2.0)

Uses: dplyr, lubridate, magrittr

Released 7 months ago.

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