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Inferential Network Analysis by Skyler J. Cranmer
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Inferential Network Analysis

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Description

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.

Author Biography:

Skyler J. Cranmer is the Carter Phillips and Sue Henry Professor of Political Science at The Ohio State University. Bruce A. Desmarais is the DeGrandis-McCourtney Early Career Professor in Political Science at Penn State University. Jason William Morgan is the Vice President for Behavioural Intelligence: Aware, and visiting scholar in Political Science at The Ohio State University.
Release date NZ
November 19th, 2020
Pages
314
Audiences
  • Professional & Vocational
  • Tertiary Education (US: College)
Dimensions
151x226x18
ISBN-13
9781316610855
Product ID
33662221

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