Wilks’ phenomenon and penalized likelihood-ratio test for nonparametric curve registration


Arnak Dalalyan, Olivier Collier ;
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, PMLR 22:264-272, 2012.


The problem of curve registration appears in many different areas of applications ranging from neuroscience to road traffic modeling. In the present work, we propose a nonparametric testing framework in which we develop a generalized likelihood ratio test to perform curve registration. We first prove that, under the null hypothesis, the resulting test statistic is asymptotically distributed as a chi-squared random variable (Wilks’ phenomenon). We also prove that the proposed test is consistent, extiti.e., its power is asymptotically equal to 1. Finite sample properties of the proposed methodology are demonstrated by numerical simulations.

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