# Universal inference

@article{Wasserman2020UniversalI, title={Universal inference}, author={Larry A. Wasserman and Aaditya Ramdas and Sivaraman Balakrishnan}, journal={Proceedings of the National Academy of Sciences}, year={2020}, volume={117}, pages={16880 - 16890} }

Significance Most statistical methods rely on certain mathematical conditions, known as regularity assumptions, to ensure their validity. Without these conditions, statistical quantities like P values and confidence intervals might not be valid. In this paper we give a surprisingly simple method for producing statistical significance statements without any regularity conditions. The resulting hypothesis tests can be used for any parametric model and for several nonparametric models. We propose…

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