May 8, 2024, 4:45 a.m. | Anton Rask Lundborg, Ilmun Kim, Rajen D. Shah, Richard J. Samworth

stat.ML updates on arXiv.org arxiv.org

arXiv:2211.02039v4 Announce Type: replace-cross
Abstract: Testing the significance of a variable or group of variables $X$ for predicting a response $Y$, given additional covariates $Z$, is a ubiquitous task in statistics. A simple but common approach is to specify a linear model, and then test whether the regression coefficient for $X$ is non-zero. However, when the model is misspecified, the test may have poor power, for example when $X$ is involved in complex interactions, or lead to many false rejections. …

abstract arxiv covariance lean linear linear model math.st regression significance simple statistics stat.me stat.ml stat.th test testing type variables

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