Comparison of nonlinear and linear PCA on surface wind, surface height, and SST in the South China Sea
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
Chen et al. (2010) applied NLPCA on SST in the South China Sea and showed that it accounts for more variance than linear PCA and brings a finer analysis of interannual variability.
“Also, in the South China Sea, Chen et al. (2010) applied NLPCA on SST and showed that this statistical method accounts for more variance of the total variables in comparison with linear PCA and brings a finer analysis of interannual variability.”
From Sea surface temperature patterns in the Tropical Atlantic: Principal component analysis and nonlinear principal component analysis (2017) · cites this paper as Chen et al. (2010)
Cited by
Sorted by citations
Kenfack, C. S., Mkankam, F. K., Alory, G., Penhoat, Y. D., Hounkonnou, M. N., Vondou, D. A., & Jr., B. G. N. (2017) · Terrestrial, Atmospheric and Oceanic Sciences · doi:10.3319/tao.2016.08.29.01 · Cited by 5 · see citing works
- Authors
- Chen, H., Yin, B., Fang, G., & Wang, Y.
- Affiliations
- Chinese Academy of Sciences (CN)
- First Institute of Oceanography (CN)
- Corresponding author
- Yin, Baoshu
- Venue
- Chinese Journal of Oceanology and Limnology
- Published
- 2010-09
- Volume
- 28
- Issue
- 5
- Pages
- 981-989
- ISSN
- 0254-4059 (ISSN-L)
- 1993-5005
- OpenAlex
- W1525340597
- Cited by
- 1
- References
- 0
- Citations by year
- 2017: 1
- FWCI
- 0.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Chinese Journal of Oceanology and Limnology (publishedVersion)
- Chinese Journal of Oceanology and Limnology
- Topics
- Physical Sciences › Earth and Planetary Sciences › Oceanography › Oceanographic and Atmospheric Processes
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
- Keywords
- nonlinear principal component analysis, sea level anomalies, sea surface temperature anomalies, South China Sea, feedforward neural networks
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.
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