Network vector autoregression
type: Item
instance of: scholarly article
title: Network vector autoregression
zbMATH Open document ID: 1381.62256
DOI: 10.1214/16-AOS1476
author: Xuening Zhu
author: Rui Pan
author: Guodong Li
author: Yuewen Liu
author: Hansheng Wang
published in: The Annals of Statistics
publication date: 2017-08-03T00:00:00Z
full work available at URL: https://projecteuclid.org/euclid.aos/1497319689
review text: In this manuscript, the authors introduce a network vector autoregressive (NAR) model to model some popular network structures including large-scale social networks. Two different types of stationarity are considered, when the network size is fixed and when the network size tends to infinity. For both cases the stationary conditions are obtained. The unknown parameters of the NAR model are estimated by the ordinary least squares method and the asymptotical normality of the obtained estimators is proved. Some potential applications to existing structures are discussed. At the end of the paper, some numerical simulations are provided to check the finite sample performance of the proposed methodology.
reviewed by: Miroslav M. Ristić
Mathematics Subject Classification ID: 62M10
Mathematics Subject Classification ID: 62J05
zbMATH DE Number: 6756075
zbMATH Keywords: network vector autoregressive model
zbMATH Keywords: network structures
zbMATH Keywords: social networks
zbMATH Keywords: multivariate times series
zbMATH Keywords: stationarity
zbMATH Keywords: ordinary least squares estimation
zbMATH Keywords: asymptotic normality
MaRDI profile type: Publication
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description: scientific article; zbMATH DE number 6756075