Inferential network analysis /
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...
| Main Authors: | , , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Cambridge ; New York :
Cambridge University Press,
[2021]
|
| Series: | Analytical methods for social research.
|
| Subjects: |
| Summary: | 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. |
|---|---|
| Physical Description: | xxiii, 291 pages : illustrations ; 24 cm. |
| Bibliography: | Includes bibliographical references (pages 272-287) and index. |
| ISBN: | 9781107158122 1107158125 9781316610855 1316610853 |