clr v0.1.1


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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) <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.



R package for Curve Linear Regression

Functions in clr

Name Description
clr-package Curve Linear Regression
clrdata Create an object of clrdata
clust_test Electricity load example: clusters on test set
predict.clr Prediction from fitted CLR model(s)
clust_train Electricity load example: clusters on train set
gb_load Electricity load from Great Britain
clr Curve Linear Regression via dimension reduction
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Type Package
Copyright EDF R&D 2017
License LGPL (>= 2.0)
Encoding UTF-8
LazyData true
RoxygenNote 6.1.1
NeedsCompilation no
Packaged 2019-01-11 16:07:52 UTC; amandinepierrot
Repository CRAN
Date/Publication 2019-01-11 16:20:03 UTC

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