The paper proposes EFRM, a scalar-on-function regression that optimizes a norm-preserving time warping of predictors inside the model and shows improved prediction RMSE on simulated and real datasets.
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Regression Models Using Shapes of Functions as Predictors
The paper proposes EFRM, a scalar-on-function regression that optimizes a norm-preserving time warping of predictors inside the model and shows improved prediction RMSE on simulated and real datasets.