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.


R package for Curve Linear Regression

News

clr 0.1.1

  • Fix small bug in clrdata(): to deal with Winter daylight saving times
  • Add precisions in clrdata() description

Reference manual

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install.packages("clr")

0.1.1 by Amandine Pierrot, 3 months ago


Browse source code at https://github.com/cran/clr


Authors: Amandine Pierrot with contributions and/or help from Qiwei Yao , Haeran Cho , Yannig Goude and Tony Aldon.


Documentation:   PDF Manual  


LGPL (>= 2.0) license


Imports magrittr, lubridate, dplyr, stats


See at CRAN