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Graphical Models in Applied Multivariate Statistics
Abstract
The Wiley Paperback Series makes valuable content more accessible to a new generation of statisticians, mathematicians and scientists.Graphical models--a subset of log-linear models--reveal the interrelationships between multiple variables and features of the underlying conditional independence. This introduction to the use of graphical models in the description and modeling of multivariate systems covers conditional independence, several types of independence graphs, Gaussian models, issues in model selection, regression and decomposition. Many numerical examples and exercises with solutions are included.This book is aimed at students who require a course on applied multivariate statistics unified by the concept of conditional independence and researchers concerned with applying graphical modelling techniques.
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Pedersen, H. K., Gudmundsdottir, V., Nielsen, H. B., Hyotylainen, T., Nielsen, T., Jensen, B. A. H., Forslund, K., Hildebrand, F., Prifti, E., Falony, G., et al. (2016) · Nature · doi:10.1038/nature18646 · Cited by 2,116
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Metadata
- Authors
- Goodall, C. R.
- Venue
- Technometrics
- Publisher
- Informa UK Limited
- Published
- 1991-11
- Volume
- 33
- Issue
- 4
- Pages
- 476-478
- ISSN
- 0040-1706 (ISSN-L)
- 1537-2723
- OpenAlex
- W2167826316
- Cited by
- 1,849
- References
- 0
- FWCI
- 28.03
- Type
- journal article
- Language
- en
- Open access
- closed
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- Goodall, C. R. (1991). Graphical Models in Applied Multivariate Statistics. Technometrics. https://doi.org/10.1080/00401706.1991.10484880
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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.
