Focused model selection for social networks

被引:2
作者
Pircalabelu, Eugen [1 ]
Claeskens, Gerda
机构
[1] Katholieke Univ Leuven, ORSTAT, Naamsestr 69, B-3000 Leuven, Belgium
关键词
Variable selection; Social network; Focused information criterion; Exponential random graphs; Network based models; P-ASTERISK MODELS; GOODNESS-OF-FIT; INFORMATION CRITERION; EXPONENTIAL FAMILY; LOGIT-MODELS; REGRESSION; GRAPHS; MEDICI;
D O I
10.1016/j.socnet.2016.03.002
中图分类号
Q98 [人类学];
学科分类号
030303 ;
摘要
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. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:76 / 86
页数:11
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