ArticleJournal of machine learning research : JMLR2019
Nonuniformity of P-values Can Occur Early in Diverging Dimensions.
Article in Journal of machine learning research : JMLR, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- High-Dimensional Knockoffs Inference for Time Series Data.Journal of the American Statistical Association · 2025Article
- DeepLINK: Deep learning inference using knockoffs with applications to genomics.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- RANK: Large-Scale Inference with Graphical Nonlinear Knockoffs.Journal of the American Statistical Association · 2020Article
- IPAD: Stable Interpretable Forecasting with Knockoffs Inference.Journal of the American Statistical Association · 2020Article
- A modern maximum-likelihood theory for high-dimensional logistic regression.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Evaluating the joint significance of covariates is of fundamental importance in a wide range of applications. To this end, p-values are frequently employed and produced by algorithms that are powered by classical large-sample asymptotic theory. It is well known that the conventional p-values in Gaussian linear model are valid even when the dimensionality is a non-vanishing fraction of the sample size, but can break down when the design matrix becomes singular in higher dimensions or when the error distribution deviates from Gaussianity. A natural question is when the conventional p-values in generalized linear models become invalid in diverging dimensions. We establish that such a breakdown can occur early in nonlinear models. Our theoretical characterizations are confirmed by simulation studies.
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32190012PMC7079742What OpenQuestion holds
Registered trials
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