The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
Imputation of missing values for compositional data using classical and robust methods
Overview
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
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
Maximum Likelihood from Incomplete Data Via the EM Algorithm
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1977.tb01600.x · Cited by 50,444
Statistical Analysis With Missing Data
Lahiff, M., Little, R. J. A., & Rubin, D. B. (1989) · Journal of the American Statistical Association · doi:10.2307/2289883 · Cited by 17,265
Analysis of Incomplete Multivariate Data
Schafer, J. L. (1997) · doi:10.1201/9781439821862 · Cited by 6,012 · cited 2×
“Further details, as well as methods based on multiple regression and principal component analysis are described in Little and Rubin (2002) and Schafer (1997).”
MethodAnalysis of Incomplete Multivariate Data
Booth, D. E. (2000) · Technometrics · doi:10.1080/00401706.2000.10486013 · Cited by 5,627
Maximum likelihood estimation from incomplete data via the EM algorithm
Dempster, A. P. (1977) · Journal of the Royal Statistical Society Series A (Statistics in Society) · Cited by 4,543
Missing Value Estimation Methods for DNA Microarrays
Troyanskaya, O., Cantor, M., Sherlock, G., Brown, P., Hastie, T., Tibshirani, R., Botstein, D., & Altman, R. B. (2001) · Bioinformatics · doi:10.1093/bioinformatics/17.6.520 · Cited by 4,230
Probabilistic Principal Component Analysis
Tipping, M. E., & Bishop, C. M. (1999) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00196 · Cited by 3,679
The Statistical Analysis of Compositional Data
Piepel, G. F. (1988) · Technometrics · doi:10.1080/00401706.1988.10488337 · Cited by 3,418
Statistical Analysis With Missing Data
Lazar, N. A. (2003) · Technometrics · doi:10.1198/tech.2003.s167 · Cited by 2,458
Isometric Logratio Transformations for Compositional Data Analysis
Egozcue, J. J., Pawlowsky-Glahn, V., Mateu-Figueras, G., & Barceló-Vidal, C. (2003) · Mathematical Geology · doi:10.1023/a:1023818214614 · Cited by 1,935
Cited by
Missing value imputation: a review and analysis of the literature (2006–2017)
Lin, W.-C., & Tsai, C.-F. (2020) · Artificial Intelligence Review · doi:10.1007/s10462-019-09709-4 · Cited by 612
robCompositions: An R‐package for Robust Statistical Analysis of Compositional Data
Templ, M., Hron, K., & Filzmoser, P. (2011) · Compositional Data Analysis · doi:10.1002/9781119976462.ch25 · Cited by 372
Self-citationCarranza, E. J. M. (2011) · Journal of Geochemical Exploration · doi:10.1016/j.gexplo.2011.05.007 · Cited by 344
Bayesian-multiplicative treatment of count zeros in compositional data sets
Martín-Fernández, J.-A., Hron, K., Templ, M., Filzmoser, P., & Palarea-Albaladejo, J. (2015) · Statistical Modelling · doi:10.1177/1471082x14535524 · Cited by 263
Self-citationReimann, C., Filzmoser, P., Fabian, K., Hron, K., Birke, M., Demetriades, A., Dinelli, E., & Ladenberger, A. (2012) · Science of The Total Environment · doi:10.1016/j.scitotenv.2012.02.032 · Cited by 262
Self-citation
Metadata
- Authors
- Hron, K., Templ, M., & Filzmoser, P.
- Venue
- Computational Statistics & Data Analysis
- Publisher
- Elsevier BV
- Published
- 2010-12
- Volume
- 54
- Issue
- 12
- Pages
- 3095-3107
- ISSN
- 0167-9473 (ISSN-L)
- OpenAlex
- W2051384456
- Cited by
- 301
- References
- 34
- FWCI
- 10.11
- 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 ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Imputation of missing values for compositional data using classical and robust methods. https://app.cochat.ai/papers/10.1016/j.csda.2009.11.023
- The paper
- Hron, K., Templ, M., & Filzmoser, P. (2010). Imputation of missing values for compositional data using classical and robust methods. Computational Statistics & Data Analysis. https://doi.org/10.1016/j.csda.2009.11.023
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.