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Inferential network analysis
Paperback
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- Book Synopsis
- This unique textbook provides an introduction to statistical inference with network data. The authors present a self-contained derivation and mathematical formulation of methods, review examples, and real-world applications, as well as provide data and code in the R environment that can be customised. Inferential network analysis transcends fields, and examples from across the social sciences are discussed (from management to electoral politics), which can be adapted and applied to a panorama of research. From scholars to undergraduates, spanning the social, mathematical, computational and physical sciences, readers will be introduced to inferential network models and their extensions. The exponential random graph model and latent space network model are paid particular attention and, fundamentally, the reader is given the tools to independently conduct their own analyses.
- About The Author
- Skyler J. Cranmer is the Carter Phillips and Sue Henry Professor of Political Science at The Ohio State University.
- Product Details
-
- ISBN
- 9781316610855
- Format
- Paperback
- Publisher
- Cambridge University Press, (19 November 2020)
- Number of Pages
- 316
- Weight
- 470 grams
- Language
- English
- Dimensions
- 226 x 151 x 18 mm
- Series:
- See all books in this series
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