ArticleJournal of the American Statistical Association2023
Estimation of the number of spiked eigenvalues in a covariance matrix by bulk eigenvalue matching analysis.
Article in Journal of the American Statistical Association, 2023. 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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Robust angle-based transfer learning in high dimensions.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2025Article
- The Dyson equalizer: adaptive noise stabilization for low-rank signal detection and recovery.Information and inference : a journal of the IMA · 2025Article
- Supervised discovery of interpretable gene programs from single-cell data.Nature biotechnology · 2024Article
- Subject clustering by IF-PCA and several recent methods.Frontiers in genetics · 2023Article
- Optimally Weighted PCA for High-Dimensional Heteroscedastic Data.SIAM journal on mathematics of data science · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
The spiked covariance model has gained increasing popularity in high-dimensional data analysis. A fundamental problem is determination of the number of spiked eigenvalues,
Indexed as
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.