Universal inference
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2020/07/06
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Indian UGC (journal)
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Refrences51
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Citations52
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Larry Wasserman Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, PA 15213;Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA 15213
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Aaditya Ramdas Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, PA 15213; ORCID (unauthenticated)
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Sivaraman Balakrishnan Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, PA 15213;
Abstract
Journal Category
Science
Science (General)
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Assigning a value to a power likelihood in a general Bayesian model | Biometrika |
| 2017 | |
| A universally consistent modification of maximum likelihood | 2013 | |||
| 10.1007/978-3-642-34106-9_16 | 2012 | |||
| Advances in Neural Information Processing Systems | 2019 | |||
| Peeking at A/B Tests: Why It Matters, and What to Do about It | 2017 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
The latent cognitive structures of social networks | Network Science |
| 2024 | |
| Universal inference meets random projections: a scalable test for log-concavity | Journal of Computational and Graphical Statistics |
| 2024 | |
| Significance Tests of Feature Relevance for a Black-Box Learner | IEEE Transactions on Neural Networks and Learning Systems |
| 2024 | |
The Bayes factor surface for searches for new physics | The European Physical Journal C |
| 2024 | |
| Merging sequential e-values via martingales | Electronic Journal of Statistics |
| 2024 |
Citations Analysis
The category
Science: Mathematics: Probabilities. Mathematical statistics 38
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled A Note on Likelihood Ratio Tests for Models with Latent Variables and was published in 2020. The most recent citation comes from a 2024 study titled Universal inference meets random projections: a scalable test for log-concavity. This article reached its peak citation in 2023, with 27 citations. It has been cited in 31 different journals, 12% of which are open access. Among related journals, the Journal of the Royal Statistical Society Series B: Statistical Methodology cited this research the most, with 6 citations. The chart below illustrates the annual citation trends for this article.