The DOI matches its Crossref record.
Quadratic Forms in Random Variables: Theory and Applications.
Abstract
Textbook for a one-semester graduate course for students specializing in mathematical statistics or in multivariate analysis, or reference for theoretical as well as applied statisticians, confines its discussion to quadratic forms and second degree polynomials in real normal random vectors and matr
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Cited by
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A power approximation for the Kenward and Roger Wald test in the linear mixed model
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Metadata
- Authors
- Olkin, I., Mathai, A. M., & Provost, S. B.
- Venue
- Journal of the American Statistical Association
- Publisher
- JSTOR
- Published
- 1992-12
- Volume
- 87
- Issue
- 420
- Pages
- 1244
- ISSN
- 0162-1459 (ISSN-L)
- OpenAlex
- W2008618334
- Cited by
- 509
- References
- 0
- FWCI
- 2.76
- Type
- journal article
- Language
- en
- Open access
- closed
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Cite CoChat for the checks on this page, and the paper for its own findings.
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- CoChat. (2026). Citation check: Quadratic Forms in Random Variables: Theory and Applications. https://app.cochat.ai/papers/10.2307/2290674
- The paper
- Olkin, I., Mathai, A. M., & Provost, S. B. (1992). Quadratic Forms in Random Variables: Theory and Applications. Journal of the American Statistical Association. https://doi.org/10.2307/2290674
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.
