Dynamic Functional Regression.
Tue, 03/15/2011 - 16:01 — SomNambul
link: http://arxiv.org/abs/1103.2486
Abstract
Abstract
A characteristic feature of samples of curves is the presence of time
variability in addition to amplitude variability. The existing functional
regression methods do not handle time variability in an efficient manner. We
propose in this paper a regression method that incorporates time warping as an
intrinsic part of the model. In this way, the method attains a high predictive
power in a parsimonious and efficient manner, avoiding overfitting and
simplifying statistical inference. The properties of the estimators are studied
by simulation, and an application to the study of human lip movement is
presented.
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