# clr v0.1.0

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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.

# clr

R package for Curve Linear Regression

## Functions in clr

 Name Description clust_train Electricity load example: clusters on train set clrdata Create an object of clrdata clr Curve Linear Regression via dimension reduction predict.clr Prediction from fitted CLR model(s) gb_load Electricity load from Great Britain clr-package Curve Linear Regression clust_test Electricity load example: clusters on test set No Results!