Focused model selection for social networks

Eugen Pircalabelu and Gerda Claeskens
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Eugen Pircalabelu: Université catholique de Louvain, LIDAM/ISBA, Belgium

No 2016048, LIDAM Reprints ISBA from Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA)

Abstract: We present a focused selection method for social networks. The procedure is driven by a focus, the main quantity we want to estimate well. It represents the statistical translation of a research hypothesis into parameters of interest. Given a collection of models, the procedure estimates for each model the mean squared error of the estimator of the focus. The model with the smallest such value is selected. We present focused model selection for (i) exponential random graph models, (ii) network autocorrelation models and (iii) network regression models to investigate existing relations in social networks. Worked-out examples illustrate the methodology.

Keywords: Variable selection; Social network; Focused information criterion; Exponential random graphs; Network based models (search for similar items in EconPapers)
Pages: 23
Date: 2016-01-01
Note: In: Social Networks, vol. 46, p. 76-86 (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:aiz:louvar:2016048

DOI: 10.1016/j.socnet.2016.03.002

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