The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Principal component analysis for data containing outliers and missing elements
Overview
The claims and statistics of this paper haven’t been checked yet.
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Integrity signals
Registry
Cites
Statistics
Verification
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.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
RUBIN, D. B. (1976) · Biometrika · doi:10.1093/biomet/63.3.581 · Cited by 9,925
Robust Regression and Outlier Detection
Rousseeuw, P. J., & Leroy, A. M. (1987) · Wiley Series in Probability and Statistics · doi:10.1002/0471725382 · Cited by 5,609
Huber, P. J. (1985) · The Annals of Statistics · doi:10.1214/aos/1176349519 · Cited by 1,277
Cited by
Data-driven Soft Sensors in the process industry
Kadlec, P., Gabrys, B., & Strandt, S. (2009) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2008.12.012 · Cited by 1,845
PPCA-Based Missing Data Imputation for Traffic Flow Volume: A Systematical Approach
Qu, L., Hu, J., Li, L., & Zhang, Y. (2009) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2009.2026312 · Cited by 441
Zhu, J., Ge, Z., Song, Z., & Gao, F. (2018) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2018.09.003 · Cited by 308
A comparative study on diabetes disease diagnosis using neural networks
Temurtas, H., Yumusak, N., & Temurtas, F. (2009) · Expert Systems with Applications · doi:10.1016/j.eswa.2008.10.032 · Cited by 305
Imputation of missing values for compositional data using classical and robust methods
Hron, K., Templ, M., & Filzmoser, P. (2010) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2009.11.023 · Cited by 301
Metadata
- Authors
- Serneels, S., & Verdonck, T.
- Venue
- Computational Statistics & Data Analysis
- Publisher
- Elsevier BV
- Published
- 2008-01
- Volume
- 52
- Issue
- 3
- Pages
- 1712-1727
- ISSN
- 0167-9473 (ISSN-L)
- OpenAlex
- W2053295697
- Cited by
- 171
- References
- 3
- FWCI
- 7.81
- Type
- journal article
- Language
- en
- Open access
- closed
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 ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
