Covers differentiation and integration, higher derivatives, partial derivatives, series expansion, integral transforms, convolution integrals, Laplace transforms, linear and time-invariant systems, linear ordinary differential equations, periodic functions, Fourier series and transforms, and matrix algebra.

Chapter 2 is methodological, offering a primer on multimodal network analysis. It proceeds by quickly reviewing 1-mode network analysis, paying special attention to summarizing several measures of network centrality and how they relate to power. Often, relational data that are 2-mode or multimodal are “projected” into one of the node sets. Ties are then defined by their shared relations to the second-mode nodes so that 1-mode measures of centrality and algorithms for community detection can be employed. We discuss the loss of information on structure and agency that projection entails and argue that, in many cases, projection is neither helpful nor necessary. We then proceed to detailed discussions of methods for 2-mode and 3-mode network analysis, from first principles of matrix algebra to centrality measures and core-periphery analysis; faction analysis and community detection; as well as structural/regular equivalence and blockmodeling. We conclude with a brief introduction to recent advances in statistical network modelling that facilitate inferences about multimodal networks.

Abadir and Magnus (2002, Econometric Theory) proposed a standard for notation in econometrics. The consistent use of the proposed notation in our volumes shows that it is in fact practical. The notational conventions described here mainly apply to the material covered in this volume. Further notation will be introduced, as needed, as the Series develops.