Asymptotic distribution in affiliation finite discrete weighted networks with an increasing degree sequence. (English) Zbl 1508.62070
Summary: The asymptotic normality of a fixed number of the maximum likelihood estimators (MLEs) in the affiliation finite discrete weighted networks with an increasing degree sequence has been established recently. In this article, we further derive a central limit theorem for a linear combination of all the MLEs with an increasing dimension. Simulation studies are provided to illustrate the asymptotic results.
MSC:
| 62F12 | Asymptotic properties of parametric estimators |
| 05C80 | Random graphs (graph-theoretic aspects) |
| 60F05 | Central limit and other weak theorems |
| 62E20 | Asymptotic distribution theory in statistics |
Keywords:
affiliation weighted networks; central limit theorem; increasing number of parameters; maximum likelihood estimatorsReferences:
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