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Monte Carlo Statistical Methods
Overview
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Integrity signals
Registry
Cites
Statistics
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Claims the paper makes
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Self-check
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Citations
Cited by
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Common Method Bias in PLS-SEM: A Full Collinearity Assessment Approach
Kock, N. (2015) · International Journal of e-Collaboration · doi:10.4018/ijec.2015100101 · Cited by 10,215
Vehtari, A., Gelman, A., Simpson, D., Carpenter, B., & Bürkner, P.-C. (2021) · Bayesian Analysis · doi:10.1214/20-ba1221 · Cited by 1,810
Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network
Su, Y., Zhao, Y., Niu, C., Liu, R., Sun, W., & Pei, D. (2019) · Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining · doi:10.1145/3292500.3330672 · Cited by 1,804
Toni, T., Welch, D., Strelkowa, N., Ipsen, A., & Stumpf, M. P. H. (2009) · Journal of The Royal Society Interface · doi:10.1098/rsif.2008.0172 · Cited by 1,498
Metadata
- Authors
- Robert, C. P., & Casella, G.
- Venue
- Springer Texts in Statistics
- Publisher
- Springer New York
- Published
- 2004
- ISSN
- 1431-875X (ISSN-L)
- OpenAlex
- W4292691288
- Cited by
- 4,271
- References
- 0
- FWCI
- 19.08
- Type
- book
- 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.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Monte Carlo Statistical Methods. https://app.cochat.ai/papers/10.1007/978-1-4757-4145-2
- The paper
- Robert, C. P., & Casella, G. (2004). Monte Carlo Statistical Methods. Springer Texts in Statistics. https://doi.org/10.1007/978-1-4757-4145-2
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.