Continuously Additive Models for Nonlinear Functional Regression

@inproceedings{Mller2012ContinuouslyAM,
  title={Continuously Additive Models for Nonlinear Functional Regression},
  author={Hans-Georg M{\"u}ller and Yichao Wu},
  year={2012}
}
We introduce continuously additive models, which can be motivated as extensions of additive regression models with vector predictors to the case of infinite-dimensional predictors. This approach provides a class of flexible functional nonlinear regression models, where random predictor curves are coupled with scalar responses. In continuously additive modeling, integrals taken over a smooth surface along graphs of predictor functions relate the predictors to the responses in a nonlinear fashion… CONTINUE READING

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