Optimal Whitening and Decorrelation
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
ZCA is the transformation that maximizes the similarity of the transformed data to the original, achieved by setting W = C−1/2, where C is the covariance of X.
“ZCA is the transformation which maximizes the similarity of the transformed data to the original, which is achieved by setting W = C−1/2, where C is the covariance of X.”
From Single-cell multiregion dissection of Alzheimer’s disease (2024) · cites this paper as [101]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
No references could be resolved yet.
Research works printed but not linked: 2
- Eldar, Y. C. and Oppenheim, A. V. (2003). MMSE whitening and subspace whitening. IEEE Trans. Inf. Theory, 49:1846-1851.
- Jolliffe, I. T. (2002). Principal Component Analysis. Springer, New York, 2nd edition.
Cited by
Sorted by citations
Single-cell multiregion dissection of Alzheimer’s disease
Mathys, H., Boix, C. A., Akay, L. A., Xia, Z., Davila-Velderrain, J., Ng, A. P., Jiang, X., Abdelhady, G., Galani, K., Mantero, J., et al. (2024) · Nature · doi:10.1038/s41586-024-07606-7 · Cited by 343 · see citing works
Benchmark of filter methods for feature selection in high-dimensional gene expression survival data
Bommert, A., Welchowski, T., Schmid, M., & Rahnenführer, J. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbab354 · Cited by 182 · see citing works
Evaluating batch correction methods for image-based cell profiling
Arevalo, J., Su, E., van Dijk, R., Carpenter, A. E., & Singh, S. (2023) · doi:10.1101/2023.09.15.558001 · Cited by 89 · see citing works
Linear and non-linear Modified Gravity forecasts with future surveys
Casas, S., Kunz, M., Martinelli, M., & Pettorino, V. (2017) · Physics of the Dark Universe · doi:10.1016/j.dark.2017.09.009 · Cited by 48 · see citing works
- Authors
- Kessy, A., Lewin, A., & Strimmer, K.
- Affiliations
- Statistics Section, Department of Mathematics, Imperial College London, South Kensington Campus, London, United Kingdom
- Department of Mathematics, Brunel University London, Kingstone Lane, Uxbridge, United Kingdom
- Epidemiology and Biostatistics, School of Public Health, Imperial College London, Norfolk Place, London, United Kingdom
- Venue
- The American Statistician
- Publisher
- Informa UK Limited
- Published
- 2018-01-26
- Volume
- 72
- Issue
- 4
- Pages
- 309-314
- ISSN
- 0003-1305
- 1537-2731
- Cited by
- 376
- References
- 0
- Language
- en
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
